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By

Chanunya Neammalai

An Independent Study Submitted in Partial Fulfillment of the Requirements for the Degree MASTER OF SCIENCE Department of Computing Graduate School SILPAKORN UNIVERSITY 2010 ´–”·˜ª·š¥µ¨´¥ ¤®µª·š¥µ¨¥«´ ·¨žµ„¦ °œ»¤´˜·Ä®o„µ¦‡œ‡ªo µ°o ·­¦³Á¦ºÉ°Š “¦³ Ÿ¼oÁ¸É¥ªµ­µ®¦Î ´‹µÂœ„œÎ ·—®°¥œÊµ‹Î º—ªŠ« r Thiaridae” Á­œ°Ã—¥ œµŠ­µªœµ´ Áœ¸¥¤¤µ¨´¥ ÁžÈœ­ªœ®œn ¹ÉŠ °Š„µ¦«¹„¬µ˜µ¤®¨´„­¼˜¦ž¦·µª·š¥µ«µ­˜¦¤®µ–”´ ·˜ ­µ µª·µÁš‡ÃœÃ¨¥¸ ­µ¦­œÁš«

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Š 49309310 : MAJOR : INFORMATION TECHNOLOGY KEY WORDS : EXPERT SYSTEM/PRODUCTION RULE/FAMILY THIARIDAE CHANUNYA NEAMMALAI : A WEB - BASED EXPERT SYSTEM FOR IDENTIFICATION OF FRESHWATER SNAILS FAMILY THIARIDAE. INDEPENDENT STUDY ADVISOR : SUNEE PONGPINIGPINYO, Ph.D. 111 pp.

This thesis presents an Expert System applied to biology. The system is developed to identify freshwater snails of Family Thiaridae 17 species of including freshwater snails Family Thiaridae. The malacology expert can insert new photos and new knowledge of freshwater snails into the system. The knowledge base will be updated automatically. The inference process in this expert system uses the forward chaining approach and the knowledge is represented in form of production rules. The system is enhanced with photos that assist not only inexperienced users but also researchers in the precise and quick identification of freshwater snails. The system is developed as a web-based expert system so it is easy usage of users and it can be used in education of biology or other subject areas. The expert system developed as a result of this research shows that the accuracy of the images recognition of 17 species of freshwater snails Family Thiaridae is 87.42%. The system performance is measured by user satisfaction. The satisfaction of malacology experts is at good level with average 4.18 and the satisfaction of general users is at good level with average 4.24. Over all the system performance is at good level with average 4.21

Department of Computing Graduate School, Silpakorn University Academic Year 2010 Student's signature ...... Independent Study Advisor's signature ...... จ „·˜˜·„¦¦¤ž¦³„µ«

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10

Ĝ˜n¨³ ´Êœ˜°œ „µ¦Á¨º°„Á‡¦ºÉ°Š¤º°­Îµ®¦´Äo¡´•œµ¦³ ‹¹Š˜o°Š˜°­œ°ŠÁš‡œ·‡„µ¦¡´•œµ ¦³ÄœÂ˜n¨³ ´Êœ˜°œ—oª¥ 1.3.4 „µ¦Âšœ‡ªµ¤¦ ¼o (Knowledge representation) ®¨´Š‹µ„Ÿnµœ„µ¦­„´—°Š‡r‡ªµ¤¦¼o ‹œÅ—o°Š‡r‡ªµ¤¦¼oš¸É­µ¤µ¦™œÎµ¤µÄo„oÅ ž{®µÂ¨³Ä®o‡ÎµÂœ³œÎµÅ—o °Š‡r‡ªµ¤¦¼oÁ®¨nµœ¸Ê˜o°ŠœÎµ¤µ Á oµ­¼n„¦³ªœ„µ¦„µ¦Âšœ‡ªµ¤¦¼o Á¡ºÉ°Ä®o°¥¼nĜ¦¼žÂš¸É‡°¤¡·ªÁ˜°¦r­µ¤µ¦™œÎµ‡ªµ¤¦¼oÁ®¨nµœ¸Ê Şčoŗ o „µ¦Âšœ‡ªµ¤¦¼o¤¸Áš‡œ·‡š¸Éčo®¨µ¥ª·›¸ Ánœ „µ¦Âšœ‡ªµ¤¦ÂÃ‡¦Š ¼o nµ¥Á·Š‡ªµ¤®¤µ¥ (Semantic networks) „µ¦Âšœ‡ªµ¤¦¼o„‘„µ¦Ÿ¨·˜ (Production Rules) „µ¦Âšœ‡ªµ¤¦¼o „¦° (Frame) Áž}œ˜oœ Ĝ œ˜°œœ´Ê ¸Ê‹³¤¸„µ¦­„´—°Š‡r‡ªµ¤¦ ¼o (Knowledge acquisition) Á¡·É¤Á˜·¤°¸„ Ÿnµœ„µ¦šÎµ˜oœÂ¦³Ÿ¼oÁ¸É¥ªµ (Prototype development) ÁœºÉ°Š‹µ„„µ¦­¦oµŠ˜oœÂ¦³šÎµ Ä®š¦µªo nµ°Š‡r‡ªµ¤¦¼oš¸ÉœÎµ¤µÄo™¼„˜o°Š Á¡¸¥Š¡° ¨³¦³­µ¤µ¦™šµŠµœÅ—Î o˜¦Š˜µ¤‡ªµ¤˜o°Š„µ¦ š¸É„ε®œ—Ūo®¦º°Å¤ n „µ¦šªœ­° ¨³„µ¦¦´¦°Š‡ªµ¤™¼„˜o°Š °Š¦³ 1.3.5 (Verification) (Validation) ´Êœ˜°œœ¸ÊĜªŠ‹¦„µ¦¡´•œµ¦³Ÿ¼oÁ¸É¥ªµ Áš¸¥Å—o„´ ´Êœ˜°œ„µ¦š—­° (Software Testing)

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¦³ ­nªœ„µ¦¦´¦°Š‡ªµ¤™¼„˜o°Š °Š¦³ (Validation) Á„¥ª„¸É ´„µ¦˜¦ª‹­°ªnµ¦³­µ¤µ¦™ čo°Š‡r‡ªµ¤¦¼oš¸É‹´—Á„ȝĜ“µœ‡ªµ¤¦¼oĜ„µ¦Ä®o‡Îµž¦¹„¬µž{®µ ¨³­µ¤µ¦™Â„ož{®µÅ—oÁ­¤º°œ

„µ¦Â„Å žo {®µÃ—¥Ÿ¼oÁ¥ªµš¸É ¸ÉÁžœ¤œ} ¬¥» r®¦º°Å¤ n Ÿ¨¨´¡›r‹µ„ ´Êœ˜°œœ¸Ê­µ¤µ¦™œÎµÅžÄÁžo œ } °¤o ¼¨ °Š ´Êœ˜°œ„µ¦­„´—°Š‡r‡ªµ¤¦ ¼o Ĝ­nªœ„µ¦Âšœ‡ªµ¤¦Å—¼o o Ž¹ÉŠ®µ„°Š‡r‡ªµ¤¦¼oš¸É¤¸Å¤­µ¤µ¦™Â„n oÅ ž{®µÅ—o‡¦°‡¨»¤ ‹ÎµÁž}œ‹³˜o°ŠÂ„oÅ °Š‡r‡ªµ¤¦¼oĜ­ªœ„µ¦Âšœ‡ªµ¤¦n ¼o‹œ„¦³šŠ¦³´É ­µ¤µ¦™ Ä®o‡Îµž¦¹„¬µž{®µÅ—o¨³Ä®oŸ¨„µ¦Ä®o‡ÎµÂœ³œÎµš¸É™¼„˜°Šo 1.3.6 „µ¦œÎµ¦³ÅžÄo‹¦·Š (Implementation) Áž}œ„µ¦ÄoŠµœ¦³Ÿ¼oÁ¸É¥ªµš¸É ¡´•œµ ¹ÊœÁ¡ºÉ°Ä®o‡ÎµÂœ³œµÄœ„µ¦Â„Î oÅ ž{®µ„´Ÿ¼očo Ž¹ÉŠª·«ª„¦°Š‡r‡ªµ¤¦¼o‹³¤¸®œoµš¸É­´ŠÁ„˜ ˜¦ª‹­°ž{®µšÁ„¸É — · ¹Êœ¦³®ªµŠ„µ¦Än oŠµœ ¨³ž¦´ž¦»ŠÂ„oÅ Ä®o„¨µ¥Ážœ¦³š} ¸É¤¸‡ªµ¤­¤¼¦– r 1.3.7 „µ¦Îµ¦»Š¦´„¬µ¦³ (Maintenance) Áž}œ ´Êœ˜°œ­»—šoµ¥ °ŠªŠ‹¦¡´•œµ ¦³Ÿ¼oÁ¸É¥ªµ ®¨´Š‹µ„š¸ÉœÎµ¦³ÅžÄo‹¦·ŠÂ¨oª °µ‹¤¸„µ¦Á¡·É¤Á˜·¤ ®¦º°Áž¨¸É¥œÂž¨Š °Š °Š‡r‡ªµ¤¦ ¼o —´Šœ´Êœ‹Š˜¹ o°Š¤¸„µ¦ž¦´ž¦»ŠÂ„oÅ “µœ‡ªµ¤¦¼oÄ®o¤¸‡ªµ¤Áž}œž{‹‹»œ°¥´ ¼nÁ­¤° Á¡°­µ¤µ¦™ºÉ Ä®o‡ÎµÂœ³œÎµ˜°Ÿn ¼očoŗo°¥nµŠ™¼„˜o°Š

11

Problem identification

Preliminary requirements analysis and knowledge acquisition

Selection of expert system tools

Representation Knowledge acquisition Prototype development

Verification and validation

Implementation

Operation and maintenance

£µ¡š ¸É 2 ªŠ‹¦„µ¦¡´•œµ¦³Ÿ¼oÁ¸É¥ªµ

š¸É¤µ : Elias M. Award, Building expert systems : principles, procedures, and applications

(United States : West publishing company, 1996), 99.

1.4 „µ¦­„´—°Š‡r‡ªµ¤¦ ¼o (Knowledge acquisition) „µ¦­„´—°Š‡r‡ªµ¤¦¼oÁž}œ„¦³ªœ„µ¦­„´— ª·Á‡¦µ³®r ¨³Âž¨‡ªµ¤¦¼o®¦º° ž¦³­„µ¦–r °ŠŸ¼oÁ¸É¥ªµš¸ÉčoĜ„µ¦Â„ož{®µ ¦ª¤Åž™¹Š„µ¦¦ª¦ª¤‡ªµ¤¦¼o‹µ„®¨nŠ‡ªµ¤¦¼o °ºÉœÇ Ánœ®œ´Š­º° ˜Îµ¦µ Á¡ºÉ°œÎµ¤µ­¦oµŠÁž}œ“µœ‡ªµ¤¦¼oš¸É‹³ÄoĜ„¦³ªœ„µ¦®µÁ®˜»Ÿ¨ (Award 1996 : 103) ‡ªµ¤­µ¤µ¦™Â¨³‡ªµ¤¦nª¤¤º° °ŠŸ¼oÁ¸É¥ªµ Áž}œž{‹‹´¥®¨´„š¸ÉšÎµÄ®o„µ¦­„´— ‡ªµ¤¦¼o‹µ„Ÿ¼oÁ¸É¥ªµž¦³­Ÿ¨­ÎµÁ¦È‹ Ž¹ÉŠª·«ª„¦°Š‡r‡ªµ¤¦¼o˜o°Šª·Á‡¦µ³®r o°ÁšÈ‹‹¦·Š°°„‹µ„ o°‡·—Á®Èœ °ŠŸ¼oÁ¸É¥ªµ Á¡ºÉ°Ä®oŗo o°¤¼¨š¸É™¼„˜o°Š ¤nœ¥Îµ œ°„‹µ„œ¸Ê¥´Š˜o°Š‡Îµœ¹Š™¹Š„µ¦Â„ož{®µ Ĝ„¦–¸š¸É¤¸‡ªµ¤‡¨»¤Á‡¦º°Á„·— ¹Êœ—oª¥ ­Îµ®¦´‹ÎµœªœŸ¼oÁ¸É¥ªµœ´Êœ°µ‹¤¸Ÿ¼oÁ¸É¥ªµ¤µ„„ªnµ 1 ‡œÅ—o ®µ„ž{®µ¤¸‡ªµ¤Ž´Žo°œ ®¦º°Áž}œŠµœš¸É¤¸‡ªµ¤­Îµ‡´

12

ª·«ª„¦°Š‡r‡ªµ¤¦¼o (Knowledge engineering) Áž}œŸ¼o¤¸šµš­Îµ‡´Äœ„µ¦¡´•œµ ¦³Ÿ¼oÁ¸É¥ªµ Ž¹ÉŠÁž}œŸ¼o„ε®œ— °Á ˜ °Šž{®µ —¹Š‡ªµ¤¦¼o¨³ž¦³­„µ¦–rš¸ÉčoĜ„µ¦ „ož{®µ‹µ„Ÿ¼oÁ¸É¥ªµ¤µÂž¨ŠÁž}œÃž¦Â„¦¤‡°¤¡·ªÁ˜°¦ r „µ¦—¹Š°Š‡r‡ªµ¤¦¼o¤¸ ´Êœ˜°œ­Îµ‡´ 3 ´Êœ˜°œÅ—o„ n 1. „µ¦¡·‹µ¦–µÄoÁ‡¦ºÉ°Š¤º°Á¡ºÉ°‡´—„¦°Š°Š‡r‡ªµ¤¦¼oš¸É‹ÎµÁž}œ˜n°„µ¦ÄoŠµœ°°„¤µ ‹µ„Ÿ¼oÁ¸É¥ªµ 2. „µ¦Âž¨‡ªµ¤ o°¤¼¨­µ¦­œÁš«š¸Éŗ‹µ„Ÿo ¼oÁ¸É¥ªµ ×¥šÎµ„µ¦‡´—Â¥„ o°‡·—Á®Èœ °ŠŸ¼oÁ¸É¥ªµ°°„‹µ„‡ªµ¤¦¼o¨³„¦³ªœ„µ¦®µÁ®˜»Ÿ¨ 3. „µ¦­¦oµŠ„‘š¸ÉœÎµÁ­œ°„¦³ªœ„µ¦Â„ož{®µ °ŠŸ¼oÁ¸É¥ªµ Áš‡œ·‡š¸ÉčoĜ„µ¦—¹Š‡ªµ¤¦¼o¤¸®¨µ¥œ·— ˜nÁš‡œ·‡š¸ÉÁž}œš¸Éœ·¥¤¤µ„š¸É­»— Ž¹ÉŠÁž}œš¸É ¦¼o‹´„„´œ¤µœµœ ‡º° „µ¦ÄoÁš‡œ·‡„µ¦­´¤£µ¬–r ×¥„µ¦­´¤£µ¬–r¤¸š´ÊŠ¦¼žÂš¸É¤¸Ã‡¦Š­¦oµŠ ¨³ÂÅ¤n¤¸Ã‡¦Š­¦oµŠ (The Structured Interview) (The Unstructured Interview) „µ¦­´¤£µ¬–r¤¸Ã‡¦Š­¦oµŠ Áž}œ„µ¦­´¤£µ¬–rš¸É¤¸„µ¦„ε®œ— o°‡Îµ™µ¤Åªo

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š¸Éčo‹³Áž}œ‡Îµ™µ¤ÂÁžd— (open-ended question) Ážd—„ªoµŠÄ®oŸ¼o˜°Å—o­—Š‡ªµ¤‡·—Á®Èœ o°—¸ °Š„µ¦ÄoÁš‡œ·‡„µ¦­´¤£µ¬–r ‡º° Ážd—ð„µ­Ä®oŸ¼oÁ¸É¥ªµ­µ¤µ¦™Â­—Š

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13

Ťn ¹Êœ˜n°„´œ ­µ¤µ¦™Á¡·É¤ ¨ „oÅ ‡ªµ¤¦¼oŗoץŤn„¦³š˜n°„µ¦šÎµŠµœ ¨³Šnµ¥˜n°„µ¦ ˜¦ª‹­°Â„oÅ o°Ÿ·—¡¨µ—š¸ÉÁ„·— ¹Êœ „µ¦Âšœ‡ªµ¤¦¼o¤¸®¨µ¥ª·›¸ ŗo„n ǦŠ­¦oµŠÁ·Š‡ªµ¤®¤µ¥ (Semantic Network), „¦° (Frames) , „‘„µ¦Ÿ¨·˜ (Production Rules) Áž}œ˜oœ Ž¹ÉŠÂ˜n¨³ª·›¸„Ȥ¸¨´„¬–³ ¨³ o°—¸ o°—o°¥ ˜„˜nµŠ„´œ „µ¦Á¨º°„čoª·›¸„µ¦Âšœ‡ªµ¤¦¼oÄ—œ´Êœ ¹Êœ°¥¼n„´¨´„¬–³‡ªµ¤¦¼o ž¦³­·š›·£µ¡Äœ „µ¦—¹Š‡ªµ¤¦¼o¤µÄ o ‡ªµ¤¥º—®¥»nœ ¨³ ´Êœ˜°œª·›¸Äœ„µ¦Â„ož{®µ ¦µ¥¨³Á°¸¥—ª·›¸„µ¦Âšœ‡ªµ¤¦¼oĜ ˜n¨³ª·›¸ ¤¸—´Šœ ¸Ê 1.5.1 ǦŠ nµ¥Á·Š‡ªµ¤®¤µ¥ (Semantic Network) Áž}œ„µ¦Âšœ‡nµ‡ªµ¤­´¤¡´œ›r °Šª´˜™» (Object) ץ˜n¨³ª´˜™»‹³Âšœ—oª¥‹»—˜n° (nodes) čo­´¨´„¬–rªŠ„¨¤Âšœ‹»—˜n° ¨³ ˜n¨³‹»—˜n°¤¸¨´„¬–³Áž}œ°³˜°¤ (Atomic) œ´Éœ‡º° ˜¨³‹n »—˜n°Ážœª} ´˜™»š¸ÉŤn­µ¤µ¦™ÂnŠÂ¥„Áž}œ ‡nµ¥n°¥Å— o ¨³‹³¤¸‡nµÁž}œ‹¦·Š ®¦º°ÁšÈ‹ ­nªœ‡ªµ¤­´¤¡´œ›r °ŠÂ˜n¨³‹»—˜n°Âšœ—ª¥Á­o oœ¨¼„«¦ (arcs) „ε®œ—š·«šµŠ „µ¦„ε®œ—‡ªµ¤­´¤¡´œ›¦³®ªr nµŠÃ®œ— Áž}œ­nªœ­Îµ‡ °Š„µ¦Âšœ‡ªµ¤¦´ ¼oœ¸Ê

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14

Aircraft

AKO AKO AKO

round Has-shape balloon Propeller jet driven AKO AKO AKO AKO AKO AKO

Ellipsoidal Has-shape blimp Special DC-3 DC-9 Concorde

IS-A IS-A IS-A

Goodyear Spirit of Air

Blimp St.Louis Force1

£µ¡š ¸É 3 ǦŠ nµ¥Á·Š‡ªµ¤®¤µ¥

š¸É¤µ : J. Giarratano and G. Riley, Expert systems : Principle and programming, 3rd ed. (Boston :

PWS, 1989),65.

ª´˜™» °Š‡¨µ­Ä—Ç ­µ¤µ¦™¤¸¨´„¬–³ž¦³‹Îµ (Attribute) Á—¸¥ª ®¦º°®¨µ¥ ¨´„¬–³ž¦³‹Îµ„Èŗo Ž¹ÉŠ‹³¤¸‡nµ °Š¨´„¬–³ž¦³‹Îµœ´ÊœÇ ¨´„¬–³ž¦³‹ÎµÂ¨³‡nµ °Š¤´œ‹³ž¦³„° „´œ ¹ÊœÁž}œ‡»–­¤´˜· °Šª´˜™» ˜´ª°¥nµŠÁnœ ‹µ„£µ¡š¸É 3 °¨¨¼œ¤¸¨´„¬–³ž¦³‹Îµ ŗo„n œµ— œÊ宜´„ ¦¼ž¦nµŠ ­¸ ‡nµ °Š Attribute ¦¼ž¦nµŠ ‡º° š¦Š¦¼žÅ n ®¦º°„¨nµªÅ—oªnµ °¨¨¼œ¤¸‡»–­¤´˜· ‡º° ¦¼ž¦nµŠÁž}œ¦¼žÅ n Áž}œ˜oœ o°—¸ °Š„µ¦Âšœ‡ªµ¤¦¼o—oª¥Ã‡¦Š nµ¥Á·Š‡ªµ¤®¤µ¥ ‡º° ­µ¤µ¦™®µÁ®˜»Ÿ¨ Ÿnµœ„µ¦™nµ¥š°—‡»–­¤´˜· °Šª´˜™»Å—o „µ¦™nµ¥š°—‡»–­¤´˜·‹³„¦³šÎµŸnµœ„µ¦ÁºÉ°¤Ã¥Š ‡ªµ¤­´¤¡´œ›r¦³®ªnµŠª´˜™»˜nµŠÇ ˜n„È¥´Š¤¸ o°‹Îµ„´—Äœ¤µ˜¦“µœ °Š„µ¦„ε®œ—ºÉ° °Š„µ¦ÁºÉ°¤Ã¥Š (Link) ÁœºÉ°Š‹µ„„µ¦„ε®œ—ºÉ° °Š„µ¦ÁºÉ°¤Ã¥ŠµŠ‡¦´ÊŠ°µ‹šÎµÄ®o¥µ„˜n°„µ¦Á oµÄ‹ ¦ª¤š´ÊŠ„µ¦Ä®o ºÉ° °Š‹»—˜n° (Node) „Șµ¤ Ánœ „µ¦„ε®œ—ºÉ°‹»—˜n°ªnµ “Chair” Ž¹ÉŠšÎµÄ®oÁ„·—‡ªµ¤„優¤Äœ ‡ªµ¤®¤µ¥ Ž¹ÉŠ°µ‹‹³®¤µ¥™¹Š‡¨µ­ ®¦º°®¤µ¥™¹ŠÂœª‡·— ®¦º°®¤µ¥™¹ŠŸ¼oÁž}œž¦³›µœÄœ„µ¦ž¦³»¤

15

‹µ„ž{®µœ¸ÊšÎµÄ®o¥µ„˜n°„µ¦Á ¸¥œÃž¦Â„¦¤®µ„Ťn¤¸„µ¦„ε®œ—ºÉ°š¸É´—Á‹œÂ¨³­ºÉ°‡ªµ¤®¤µ¥ Á¡¸¥Š¡° (Giarratano and Riley 1998 : 72) 1.5.2 „¦° (Frame) „µ¦Âšœ‡ªµ¤¦¼o—oª¥„¦°Áž}œ„µ¦Âšœ‡ªµ¤¦¼oĜ¨´„¬–³ ǦŠ­¦oµŠ¨Îµ—´´Êœ Ž¹ÉŠÁž}œ„µ¦Âšœ‡ªµ¤¦¼o¦ª¤„´œ¦³®ªnµŠ‡ªµ¤¦¼oÁ·Šž¦³„µ« (Declarative Knowledge) ¨³‡ªµ¤¦¼oÁ·Š¦³Á¥ª¸ ·›¸ (Procedural Knowledge) šÎµÄ®oŠnµ¥˜°‡ªµ¤Á n µÄ‹Äœ °Á ˜o °Šž{®µ (Award 1996 : 250) Ž¹ÉŠ„µ¦Âšœ‡ªµ¤¦¼o„¦°‹³Ážœ„µ¦Â­—Š™} ¹Š­·ÉŠ˜nµŠÇ š¸É¤¸°¥¼nĜ 脇ªµ¤Áž}œ‹¦·Š Ánœ ¡œ„Šµœ´ »‡¨¨ ®¦º°ž¦³Á£š °Š»‡‡¨ „¦°™¼„¡´•œµ ¹ÊœÃ—¥ Marvin Minsky ‹µ„Âœª‡·—š¸É¤¸„µ¦®µÁ®˜»Ÿ¨ —oª¥ „µ¦¡´•œµÁž}œ¦³Ä®¤n š¸Éŗo¦´Ã‡¦Š­¦oµŠ‹µ„®œnª¥‡ªµ¤‹Îµ‹µ„¦³Á—·¤Ã‡¦Š­¦oµŠ °Š„¦° ‹¹Šž¦³„°—oª¥ 2 ­nªœ ŗo„n ª´˜™»¦µ¥„µ¦š¸É˜o°Š„µ¦°›·µ¥ (Slot) ¨³ ¨´„¬–³ž¦³‹Îµš¸Éčo°›·µ¥ ª´˜™»¦µ¥„µ¦š¸É˜o°Š„µ¦°›·µ¥ (Facet) ×¥ ª´˜™»¦µ¥„µ¦š¸É˜o°Š„µ¦°›·µ¥‡º°¨´„¬–³ž¦³‹Îµ (Attribute) š¸Éčo°›·µ¥ª´˜™» ¨³Â¨³ ¨´„¬–³ž¦³‹Îµš¸Éčo°›·µ¥ª´˜™»¦µ¥„µ¦š¸É˜o°Š„µ¦°›·µ¥ Áž}œ (Facet) ‡nµ °Šª´˜™» (£µ¡š¸É 4) ˜´ª°¥nµŠÁnœ Ĝª´˜™» °ŠÄ°œ»µ˜ (License) ¤¸‡»–¨´„¬–³ °ŠŸ¼o­°œ

(Insructor) Ž¹ÉŠ‡»–­¤´˜·œ¸Ê‡º°ª´˜™»¦µ¥„µ¦š¸É˜o°Š„µ¦°›·µ¥ (Slot) ¨³‡nµ °Š‡»–­¤´˜·œ¸Ê‡º° Olesak Ž¹ÉŠÁž}œ¨´„¬–³ž¦³‹Îµš¸Éčo°›·µ¥ª´˜™»¦µ¥„µ¦š¸É˜o°Š„µ¦°›·µ¥ (Facet)

Object : License Slot Facet Instructor Olesek Verification License Unique feature of verification Seal Teaching certification Air rescue

£µ¡š ¸É 4 „µ¦Âšœ‡ªµ¤¦¼o—oª¥„¦° °ŠÄ°œ»µ˜ºÉ° “Olesek” š¸É¤µ : Elias M. Award, Building expert systems : principles, procedures, and applications (United States : West publishing company, 1996), 250.

Áš‡œ·‡„µ¦®µÁ®˜»Ÿ¨®µš¸Éčo„µ¦Âšœ‡ªµ¤¦¼o„¦°Á¦¸¥„ªnµ„µ¦‹´‡ ¼n (Matching) ¦³®ªnµŠ„¦°­°Š°´œ Ž¹ÉŠÁž}œ„µ¦‹´‡¼n‡nµ °Šª´˜™»š¸É­œÄ‹ „´‡nµ °Šª´˜™»¦µ¥„µ¦š¸É ˜o°Š„µ¦°›·µ¥ (Slot) ®µ„¤¸‡nµ˜¦Š„´œ ‹¹Š‹³­¦»žÁ®˜»„µ¦–rš¸ÉÁ„·— ¹Êœ

16

„¦°¤¸‡»–­¤´˜·Äœ„µ¦­ºš°—‡»–­¤´˜·‹µ„„¦°š¸É°¥¼nĜ¦³—´­¼Š„ªnµ ×¥‡¨µ­¨¼„­ºš°—‡»–­¤´˜·‹µ„‡¨µ­Â¤n ˜n„Ȥ¸µŠ‡»–­¤´˜·š¸ÉÁž}œ¨´„¬–³ÁŒ¡µ³ °Š‡¨µ­¨¼„ Ž¹ÉŠÅ¤nŗo™¼„čo¦nª¤„´œ„´‡¨µ­Â¤n ˜´ª°¥nµŠÁnœ „¦°ºÉ° “Performance Review” Áž}œ‡¨µ­Â¤n ž¦³„°—oª¥ª´˜™»¦µ¥„µ¦š¸É˜o°Š„µ¦°›·µ¥ (Slot) ‡º° ž¦³Á£š (Type), ›¦¦¤µ˜· (Nature), Ÿ¼o°Îµœª¥„µ¦ (Director), Attendance ¨³ ‡ªµ¤™¸É (Frequency) Ž¹ÉŠž¦³Á£š °Š„¦°ºÉ° “Performance Review” ‡º°„¦°ºÉ° “Session” —´Šœ´Êœ‡»–­¤´˜· °Š›¦¦¤µ˜· (Nature) ‹¹Š™¼„čo Ĝ„¦° “Session” Ž¹ÉŠÁž}œ‡¨µ­¨¼„—oª¥ ˜nĜ‡»–­¤´˜· °Š Ÿ¼o°Îµœª¥„µ¦ (Director), Attendance ¨³ ‡ªµ¤™ ¸É (Frequency) œ´ÊœÁž}œ¨´„¬–³ÁŒ¡µ³ °Š„¦° “Performance Review” (£µ¡š ¸É 5)

Child Frame

Session Type

Nature : informal Parent Frame Time : 10:10 A.M.

Performance Review Place : Director’s

Type is a office Session Child Frame Nature : informal Manager Director is a manager Type is a Attendance : ? Conference Frequency : ? Seniority : member of evaluation review

£µ¡š ¸É 5 ˜´ª°¥µŠ„µ¦­n ºš°—‡»–­¤´˜· °Š„¦° š¸É¤µ : Elias M. Award, Building expert systems : principles, procedures, and applications (United States : West publishing company, 1996), 252.

17

o°—o°¥š¸É­Îµ‡´ °Š„¦° ‡º° ®µ„„µ¦ÁºÉ°¤Ã¥Š¦³®ªnµŠ„¦°¤¸‡ªµ¤Ž´Žo°œ ¤µ„ „µ¦®µÁ®˜»Ÿ¨‹³˜o°ŠÄÁª¨µœµœ„ªo nµ„µ¦Âšœ‡ªµ¤¦Â°¼o ºÉœÇ ¨³„µ¦Âšœ‡ªµ¤¦¼o„¦° ¥´ŠÅ¤n­µ¤µ¦™°›·µ¥™¹Š‡ªµ¤¦¼oš¸ÉÁ„·—‹µ„­µ¤´­Îµœ¹„Å—o—¸Ášnµ„µ¦Âšœ‡ªµ¤¦¼o—oª¥„‘ 1.5.3 „‘„µ¦Ÿ¨·˜ (Production rule) „‘„µ¦Ÿ¨·˜ ¤¸„µ¦Âšœ‡ªµ¤¦¼oĜ¨´„¬–³ °Š ǦŠ­¦oµŠš¸ÉÁž}œ°·­¦³˜n°„´œ o°—¸ °Š„µ¦Âšœ‡ªµ¤¦¼oª·›¸œ¸Ê‡º° „‘­µ¤µ¦™Á ¸¥œÁžœ‡} ε­´ÉŠÁŠºÉ°œÅ š¸É Šnµ¥˜n°„µ¦Á ¸¥œÂ¨³„µ¦Á oµÄ‹ (Award 1996 : 252) ǦŠ­¦oµŠ °Š„‘ž¦³„°—oª¥­ªœn IF Á¦¥„ª¸ nµ ­nªœÁŠºÉ°œÅ ¨³­nªœ THEN ®¦º°­nªœ„µ¦„¦³šÎµ Ĝ­ªœ °ŠÁŠn ºÉ°œÅ ¤¸¨´„¬–³Áž}œ˜¦¦¦„³ (Yes/No, true/false) Ž¹ÉŠ„‘‹³™¼„ „¦³šÎµ„Șn°Á¤ºÉ°¤¸­nªœÁŠºÉ°œÅ š¸ÉÁž}œ‹¦·Š ­nªœ °ŠÁŠºÉ°œÅ œ´Êœ­µ¤µ¦™Â¥„Å—oÁž}œ®¨µ¥ÁŠºÉ°œÅ ž¦³„°„´œ ¨³™¼„¦ª¤Á µ„o ´œ—ª¥˜o ª—´ εÁœ·œ„µ¦ “AND” ®¦º° “OR” Ĝ„µ¦ž¦³¤ª¨Ÿ¨ „‘‹³™¼„ š—­°ÁŠºÉ°œÅ Ž¹ÉŠ„µ¦š—­°„‘‹³™¼„„¦³šÎµ„n°œ„µ¦„¦³šÎµÄ—Ç °Š„‘‹³™¼„ž’·´˜·„µ¦ ˜´ª°¥nµŠ °Š„‘ ŗo„n

IF GPA is “high” THEN . . .

IF car_motor is “bad” or car_body is fair THEN . . . ǦŠ­¦oµŠ °Š Production Rule ‹³ž¦³„°—oª¥­ªœ¥n °¥®¨n ´„­µ¤­nªœ ‡º°

1. “µœ„‘ (Rule Base) Áž}œ“µœ‡ªµ¤¦¼oš¸ÉÁ„ȝ‡ªµ¤¦¼oš¸É°¥¼nĜ¦¼ž °Š„‘ ­nªœ˜¸‡ªµ¤ ®¦º°­nªœ„µ¦®µÁ®˜»Ÿ¨ Ž¹ÉŠ‹³˜¦ª‹—¼ÁœºÊ°®µÄœ 2. (Interpreter) “µœ„‘¨³¡œšºÊ ¸ÉšÎµŠµœ (Working Memory) ¨oª„È‹³Á¨º°„„‘Ä—„‘®œ¹ÉŠ‹µ„ÁŽÈ˜ °Š„‘š¸É¤¸ÁŠºÉ°œÅ ‡¦ ¹Êœ¤µž’·´˜·„µ¦ 3. ¡ºÊœš¸ÉšÎµŠµœ(Working Memory) Áž}œš¸ÉÁ„ȝ o°¤¼¨Â¨³­™µœ³ °Š¦³ o°¤¼¨Â¨³­™µœ³¡ºÊœš¸ÉšÎµŠµœ‹³Áž}œ °¤o ¼¨Á oµ °Š­nªœ “IF” °Š„‘¨³™¼„°µŠ°o ·ŠÂ¨³Áž¨¸É¥œÂž¨Š ×¥„‘Äœ“µœ„‘ (Rule Base) „µ¦ž’·´˜·„µ¦Â˜n¨³‡¦´ÊŠ‹³ž¦³„°—ª¥ªŠ‹¦—o ´Š˜n°Åžœ ¸Ê 1. „µ¦‹´‡¼n (Matching) : ‹³šÎµ„µ¦˜¦ª‹ÁœºÊ°®µ °Š¡ºÊœš¸ÉšÎµŠµœ (Working Memory) ¨³“µœ„‘ (Rule Base) Á¡ºÉ°®µ„‘š´ÊŠ®¤—š¸É¤¸ÁŠºÉ°œÅ ¡¦o°¤ 2. „µ¦‹—„µ¦‡´ ªµ¤ ´—Â¥oŠ (Conflict resolution) : ‹µ„„‘š¸É®µÅ—‹µ„„µ¦‹o ´‡ ¼n (Matching) ‹³¤¸„µ¦Á¨º°„„‘š¸ÉÁ®¤µ³­¤ œ¤µ¹Ê 1 „‘ 3. „µ¦„¦³šÎµ (Action) : ž’·´˜·„µ¦˜µ¤­nªœ °Š THEN °Š„‘š¸Éŗ‹µ„„µ¦o ‡´—Á¨º°„Äœ o° 2 Ž¹ÉŠµŠ„µ¦ž’·´˜·„µ¦°µ‹‹³Áž}œ„µ¦Áž¨¥œÂž¨ŠÁœ¸É ºÊ°®µ °Š¡ºÊœš¸ÉšÎµŠµœ (Working Memory)

18

1.6 „¦³ªœ„µ¦„µ¦®µÁ®˜Ÿ¨» Áž}œ­nªœ„¦³ªœ„µ¦‡·—®µÁ®˜»Ÿ¨Ã—¥Äo‡ªµ¤¦¼oš¸É¤¸°¥¼nĜ“µœ‡ªµ¤¦¼o Á¡ºÉ°ª·Á‡¦µ³®r ¨³Â„ož{®µÃ—¥ÄoÁ®˜»Ÿ¨šµŠ˜¦¦„³­Îµ®¦´Â˜n¨³Á®˜»„µ¦–r „¦³ªœ„µ¦®µÁ®˜»Ÿ¨¤¸®¨µ¥ ž¦³Á£š ŗo„ n „µ¦®µÁ®˜»Ÿ¨Â„‘ Ž¹ÉŠÂnŠÁž}œ 2 ž¦³Á£š‡º° „µ¦®µÁ®˜»Ÿ¨ÂÅž oµŠ®œoµ ¨³ „µ¦®µÁ®˜»Ÿ¨Â¥o°œ„¨´ ­nªœª·›¸°ºÉœÇ ŗo„n „µ¦®µÁ®˜»Ÿ¨—oª¥Â‹Îµ¨°Š ¨³„µ¦Á®˜»Ÿ¨—oª¥ „¦–¸«¹„¬µ Ž¹ÉŠÂ˜n¨³ª·›¸¤¸¦µ¥¨³Á°¸¥——´Šœ ¸Ê 1.6.1 „µ¦®µÁ®˜»Ÿ¨ÂÅž oµŠ®œoµ (Forward chaining) Áž}œ„µ¦®µÁ®˜»Ÿ¨Ã—¥ Á¦·É¤˜oœ‹µ„ÁŽ˜ °Š o°¤¼¨š¸É¤¸°¥ ¼n Ş­¼n o°­¦»ž ª·›¸œ¸Ê°µ‹Á¦¸¥„ªnµÁž}œ„µ¦®µÁ®˜»Ÿ¨Ã—¥„µ¦ ´Á‡¨ºÉ°œ °Š o°¤¼¨ Ž¹ÉŠ„¦³ªœ„µ¦ž¦³¤ª¨Ÿ¨‹³Äo„µ¦Âž¨„‘ ×¥„µ¦Áž¦¸¥Áš¸¥ÁŠ°œÅ °Š„‘˜ºÉ n¨³„‘ ®µ„„‘Ä—¤¸ÁŠ°œÅ šºÉ ¸ÉÁž}œ‹¦·Š „‘œ´Êœ„È‹³™¼„ž’·´˜·„µ¦ ¨³œÎµÅž­¼n„µ¦Á¡·É¤‡ªµ¤‹¦·ŠÄ®¤n Ž¹ÉŠ°µ‹‹³ ™¼„Á¦¸¥„čo×¥„‘°ºÉœ˜n°Åž „µ¦®µÁ®˜»Ÿ¨ÂÅž oµŠ®œoµ °µ‹Á¦¸¥„Å—oªnµÁž}œ„µ¦®µ (Forward chaining) Á®˜»Ÿ¨Äœ¨´„¬–³¨nµŠ ¹Êœœ (bottom-up reasoning) ‡º° o°­¦»ž °Š­¤¤˜·“µœ ŗo¤µ‹µ„‡nµ‡ªµ¤‹¦·Š

Ĝ¦³—´„n°œ®œoµ (£µ¡š¸É 6) ¨³‡nµ‡ªµ¤‹¦·Šš¸ÉčoĜ„µ¦®µÁ®˜»Ÿ¨œ´Êœ‹´—Áž}œ‡nµ‡ªµ¤‹¦·Š ®œnª¥®œ¹ÉŠÄœ“µœ‡ªµ¤¦¼o ÁœºÉ°Š‹µ„Ťn­µ¤µ¦™ÂnŠÂ¥„Å—oÁž}œ‡nµ‡ªµ¤‹¦·Š¥n°¥Å—o°¸„ ‹µ„£µ¡

­´¨´„¬–rªŠ„¨¤Âšœ—oª¥‡nµ‡ªµ¤‹¦·Š (Facts) ¨³­´¨´„¬–r­¸ÉÁ®¨¸É¥¤‡º°„‘ (Rules) Ž¹ÉŠ„‘®œ¹ÉŠ ž¦³„°—oª¥‡nµ‡ªµ¤‹¦·ŠÄ—Ç ×¥°µ‹‹³¤¸¤µ„„ªnµ®œ¹ÉŠ‡nµ Ánœ „‘ ž¦³„°—oª¥‡nµ‡ªµ¤‹¦·Š R1 A ¨³ B „‘­nªœœ­»—‡º°„‘š¸ÉÁž}œ o°­¦ »ž (Conclusions) „µ¦®µÁ®˜»Ÿ¨‹œÅ—o o°­¦»ž­»—šoµ¥ Á¦·É¤˜oœ‹µ„„µ¦®µ‡nµ‡ªµ¤‹¦·ŠÂ˜n¨³‡nµž¦³„°Á oµ„´œÁž}œ„‘Ä—Ç ¨³„‘š¸É­¦»žÅ—o„È‹³Áž}œ‡nµ ‡ªµ¤‹¦·Š®œ¹ÉŠ °Š„‘ o°°ºÉœÇ ˜n°Åž ‹œ­»—šoµ¥Å—oÁž}œ„‘š¸ÉÁž}œ o°­¦»ž Ž¹ÉŠÁž¦¸¥Å—o„´„µ¦­¦»ž ‹µ„¨nµŠ ¹ÊœœÃ—¥Äo‡nµ‡ªµ¤‹¦·Š¡ºÊœ“µœ‹µ„¦³—´¨nµŠž¦³„°„´œ ¹ÊœÅžÁž}œ„‘¥n°¥Ç ¨³®¨µ¥Ç „‘¥n°¥ž¦³„°„´œÁž}œ„‘ o°­¦»žŽ¹ÉŠ°¥¼n¦³—´œ­»— (Giarratano and Riley 1998 : 146)

19

R8 R9 Conclusions

H J J K

R5 R6 R7 Inferred Facts

H H I

R1 R2 R3 R4

A B C D E F G Facts

£µ¡š ¸É 6 „µ¦®µÁ®˜»Ÿ¨ÂÅž oµŠ®œoµ

š¸É¤µ : J. Giarratano and G. Riley, Expert systems : Principle and programming, 3rd ed. (Boston : PWS, 1989),146.

1.6.2 „µ¦®µÁ®˜»Ÿ¨Â¥o°œ„¨´ (Backward chaining) „µ¦®µÁ®˜»Ÿ¨‹³Á¦·É¤˜oœ

‹µ„„µ¦Á¨º°„ °­¦o »ž ®¦º°Ážjµ®¤µ¥š¸ÉÁžœÅžÅ—} o ¨³¡¥µ¥µ¤‡oœ®µ®¨´„“µœš¸ÉœÎµ¤µ­¼n o°­¦»žœ´Êœ

(£µ¡š ¸É 7) ª·›¸œ¸ÊÁ¦¸¥„ªnµÁž}œ„µ¦®µÁ®˜»Ÿ¨Ã—¥„µ¦ ´Á‡¨°œ—ºÉ oª¥Ážjµ®¤µ¥ ®¦º°Á¦¸¥„ªnµ „µ¦®µÁ®˜»Ÿ¨ ‹µ„œ¨Š¨nµŠ (top-down reasoning) ‹µ„£µ¡­¤¤˜ ·“µœœ­»— H ‡º°­¤¤˜·“µœš¸ÉÁž}œ‹¦·Š „µ¦®µ

Á®˜»Ÿ¨‹³Á¦·É¤‹µ„­¤¤˜·“µœš¸ÉÁž}œ‹¦·Šœ¸ÊœÎµÅž­¼n­¤¤˜·“µœ¦³—´™´—Åž H1 H2 ¨³ H3 ×¥˜o°Š¤¸ ­¤¤˜·“µœ°¥nµŠœo°¥ 1 ­¤¤˜·“µœš¸ÉÁž}œ‹¦·Š ˜nµŠ­¤¤˜·“µœ‹³Áž}œ‹¦·Šœ´Êœ°µ‹ž¦³„°—oª¥®¨µ¥ ­¤¤˜·“µœ Ž¹ÉŠ˜o°ŠÁž}œ‹¦·ŠšŠ®¤—´Ê „¦–¸œ¸Êčo­´¨´„¬– r “¨³” ­¤¤˜·“µœÄœ¦³—¨´ nµŠš¸ÉÁž}œ ‹¦·Š ‹³Á¦¸¥„ªµÁžn }œÁžjµ®¤µ¥¥n°¥ (Subgoal) „µ¦®µÁ®˜»Ÿ¨‹³šÎµ‹µ„Ážjµ®¤µ¥®¨´„Åž­¼nÁžjµ®¤µ¥¥n°¥ ˜n°ÁœºÉ°Š„´œÅž ‹œÅž­¼n‡nµ‡ªµ¤‹¦·Š¦³—´¨µŠ­n »— (Giarratano and Riley 1998 : 147)

20

H Initial Hypothesis (Goal)

H1 H2 H3 Intermediate Hypotheses (Subgoals) H4 H5 H6

A B C D E Evidence (Facts)

£µ¡š ¸É 7 „µ¦®µÁ®˜»Ÿ¨Â¥o°œ„¨´ š¸É¤µ : J. Giarratano and G. Riley, Expert systems : Principle and programming, 3rd ed. (Boston :

PWS, 1989), 147.

1.6.3 „µ¦®µÁ®˜»Ÿ¨—oª¥Â‹Îµ¨°Š (Model-based reasoning) Áž}œ„µ¦®µÁ®˜»Ÿ¨ ‹µ„‹Îµ¨°Šš¸É­¦oµŠ ¹ÊœÃ—¥‹Îµ¨°ŠšµŠÁ¨º°„˜nµŠÇ š¸ÉčoĜ„µ¦Â„oÅ ž{®µÄœ­™µœ„µ¦–r‹¦·Š

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‡ªµ¤­³—ª„¨³¥º—®¥»nœ„ªnµ„µ¦Äo®µÁ®˜»Ÿ¨Â„‘ ×¥„µ¦®µÁ®˜»Ÿ¨—oª¥Â‹Îµ¨°Š­µ¤µ¦™ „ož{®µÂš´œš¸ (Real-time) ŗo ¨³­µ¤µ¦™ª·œ·‹Œ´¥ž{®µÅ—oš´ÊŠÂš¸ÉÁž}œž{®µš´ÉªÅž ¨³ ž{®µš¸ÉŤnž„˜·Ž¹ÉŠ˜nµŠ‹µ„„µ¦®µÁ®˜»Ÿ¨Â„‘š¸ÉĜ„µ¦Îµ¦»Š¦´„¬µ˜o°Š ¹Êœ°¥¼n„´„µ¦ž¦´ž¦»ŠÂ„oÅ “µœ„‘×¥¤œ»¬¥ r ¨³­µ¤µ¦™ª·œ·‹Œ´¥ž{®µÅ—oÁŒ¡µ³ž{®µš´ÉªÅžÁšnµœ´Êœ (Award 1996 : 293) 1.6.4 „µ¦®µÁ®˜»Ÿ¨—oª¥„¦–¸«¹„¬µ (Case-Based reasoning : CBR) Áž}œ„µ¦®µ Á®˜»Ÿ¨Ã—¥ÄoœªšµŠÂ„ož{®µÄœ°—¸˜¤µž¦´ÄoĜ„µ¦Â„ož{®µš¸ÉÁ„·— ¹ÊœÄœž{‹‹»´œ ×¥„µ¦œÎµ œªšµŠÂ„ož{®µš¸ÉĄ¨oÁ‡¸¥Šš¸É­»—š¸ÉÁ„ȝ°¥¼nĜ®œnª¥‡ªµ¤‹Îµ¤µŸnµœ„¦³ªœ„µ¦®µÁ®˜»Ÿ¨Ã—¥„µ¦ Áž¦¸¥Áš¸¥„¦–¸ž{®µÄœ°—¸˜„´ž{®µš¸ÉÁ„·— ¹ÊœÄœž{‹‹»´œ ®µ„¥´ŠÅ¤n­µ¤µ¦™®µÁ®˜»Ÿ¨Å—o ‹¹Š‹³ šÎµ„µ¦­°™µ¤‡Îµ™µ¤˜nµŠÇ ‹µ„Ÿ¼oč o „µ¦®µÁ®˜»Ÿ¨—oª¥„¦–¸«¹„¬µ¤¸ o°—¸„ªnµ„µ¦®µÁ®˜»Ÿ¨Â„‘š¸Éž¦³®¥´—Áª¨µ Ĝ„µ¦¡´•œµ¦³ ÁœºÉ°Š‹µ„„µ¦®µÁ®˜»Ÿ¨Â„‘ ‹³Äo°Š‡r‡ªµ¤¦¼o‹µ„“µœ„‘Ž¹ÉŠÅ—o¤µ‹µ„„µ¦ ­„´—°Š‡r‡ªµ¤¦¼o‹µ„Ÿ¼oÁ¸É¥ªµš¸ÉÁž}œ¤œ»¬¥r ¨³œÎµ¤µ­¦oµŠÁž}œ“µœ„‘Á¡ºÉ°œÎµ¤µ¡´•œµ¦³

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Ÿ¼oÁ¸É¥ªµ ˜nĜ„µ¦®µÁ®˜»Ÿ¨—oª¥„¦–¸«¹„¬µ‹³®µÁ®˜»Ÿ¨Ã—¥ÄoœªšµŠ„µ¦Â„ož{®µ‹µ„°—¸˜ š¸ÉÁ‡¥Á„·— ¹Êœ¤µÂ¨oª ‹¹Šnª¥¨—Áª¨µÄœ„µ¦®µÂœªšµŠÂ„oÅ ž{®µš¸ÉÁ„·— ¹Êœ šÎµÄ®o„µ¦Â„ož{®µ¤¸ ‡ªµ¤¦ª—Á¦Èª¥·ÉŠ ¹Êœ ¨³Å¤n˜o°ŠšÎµ„µ¦­„´—°Š‡r‡ªµ¤¦¼o¨³®µÂœªšµŠ„µ¦Â„ož{®µ˜´ÊŠÂ˜nÁ¦·É¤˜oœ „µ¦®µÁ®˜»—oª¥ª·›¸œ¸Ê‹³Áž}œž¦³Ã¥œr¤µ„Á¤ºÉ°‡ªµ¤¦¼oš¸É‹³œÎµ¤µÄoœ´Êœ¥µ„˜n°„µ¦­¦oµŠÁž}œ„‘ ¨³ Áž}œž{®µš¸É¤¸‡ªµ¤Å¤nœnœ°œ Ťn­°—‡¨o°Š„´œ œ°„‹µ„œ¸Ê¥´Š—¼Â¨ Îµ¦»Š¦´„¬µ“µœ‡ªµ¤¦¼oŗo­³—ª„ „ªnµÂ„‘ Á¡¸¥ŠÂ‡nÁ¡·É¤„¦–¸«¹„¬µÄ®¤nš¸É¤¸‡ªµ¤‡¨oµ¥„´„¦–¸«¹„¬µÂÁ—·¤ ¨³Á¡·É¤‡Îµ™µ¤ µŠ°¥nµŠÁ oµÅžÁšnµœ´Êœ (Award 1996 : 294) 1.7 Á‡¦ºÉ°Š¤º°Äœ„µ¦¡´•œµ¦³Ÿ¼oÁ¸É¥ªµ 1.7.1 CLIPS (Gonzalez and Dankel 1993 : 445) ®œª¥žn {µž¦³—·¬“ r (Artificial Intelligence) °Š«¼œ¥ r Johnson Space °Š NASA ŗo¡´•œµÃ‡¦Š¦³Ÿ¼oÁ¸É¥ªµ ¹ÊœºÉ° CLIPS Ž¹ÉŠÄo£µ¬µ C Ĝ„µ¦¡´•œµ ¨³Äo„¦³ªœ„µ¦®µÁ®˜»Ÿ¨ÂÅž oµŠ®œoµ (Forward Chaining) ¨³¤¸„µ¦Âšœ‡ªµ¤¦¼oĜ“µœ‡ªµ¤¦¼o„‘ ǦŠ­¦oµŠ °Š (Rule based System) CLIPS ž¦³„°—ª¥­o nªœ„µ¦‹—„µ¦‡´ nµ‡ªµ¤‹¦·Š (Facts) ­nªœ„µ¦‹´—„µ¦„‘ (Rules) ¨³­nªœ„µ¦‹—„µ¦´

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Ĝ­nªœ °Š„µ¦„ε®œ—„‘ (Rules) ­µ¤µ¦™„¦³šÎµŸnµœ‡Îµ­´ÉŠ °Š„µ¦„ε®œ— „‘ÁnœÁ—¸¥ª„´„µ¦„ε®œ—‡nµ‡ªµ¤‹¦·Š ˜n˜nµŠ„´œš¸É¦¼žÂ °Š‡Îµ­´ÉŠ ×¥„µ¦„ε®œ—„‘­µ¤µ¦™ šÎµÅ—oץčo‡Îµ­´ÉŠ defrule Ĝ­nªœ„µ¦„ε®œ—„µ¦„¦³šÎµ °Š„‘ ®¦º°­nªœ Then œ´Êœ‹³¤¸„µ¦Äo‡Îµ­´ÉŠÄœ „µ¦Á¡·É¤ ¨ ‡nµ‡ªµ¤‹¦·Š Ž¹ÉŠÄœ­nªœ °Š„µ¦¨‡nµ‡ªµ¤‹¦·Š ‹ÎµÁž}œ˜o°ŠÄo˜´ª¦³»‡nµ‡ªµ¤‹¦·Š (fact identifier) —oª¥ šÎµÄ®o¥»nŠ¥µ„Äœ„µ¦­¦oµŠ„‘ —´Šœ´Êœ CLIPS ‹¹Š¤¸Á‡¦ºÉ°Š¤º°°Îµœª¥‡ªµ¤­³—ª„˜nµŠÇ Á¡ºÉ°¦°Š¦´„µ¦šÎµŠµœÄœ„µ¦Áž¦¸¥Áš¸¥¦¼žÂÄ®o­µ¤µ¦™šÎµÅ—o­³—ª„ ¹Êœ ŗo„n „µ¦„ε®œ— ˜´ªÂž¦ Á¡ºÉ°Âšœ‡nµ‡ªµ¤‹¦·Š „µ¦Äo­´¨´„¬–r¡·Á«¬Âšœ‡nµ‡ªµ¤‹¦·ŠµŠ­nªœ ®¦º°„µ¦Ä®oŸ¼očo ­µ¤µ¦™„ε®œ—¢{Š„r´œÁ°ŠÅ— o Áž}œ˜oœ Ĝ­nªœ˜·—˜n°„´Ÿ¼očo °Š CLIPS ­µ¤µ¦™„¦³šÎµÅ—o 2 šµŠ ŗo„n „µ¦¡·¤¡r ‡Îµ­´ÉŠ CLIPS š¸É Prompt ¨³„µ¦˜·—˜n°ŸnµœÁ¤œ¼Äœ¦³ DOS Ž¹ÉŠ­µ¤µ¦™Äoŗo×¥¡·¤¡r‡Îµ­´ÉŠ Ž¹ÉŠ„µ¦˜·—˜n°Ÿ¼očoץčoÁ¤œ¼Äœ¦³ ¤¸‡ªµ¤­³—ª„˜n°„µ¦ÄoŠµœ„ªnµ¤µ„ CLPDSSZ DOS ÁœºÉ°Š‹µ„Ÿ¼očo­µ¤µ¦™Á¨º°„šÎµ­·ÉŠ˜nµŠÇ ŗoץčoÁ¤µ­r¨³‡¸¥r°¦r—Å—o ®¦º°ÄoŠµœŸnµœ ‡¸¥r¨´—˜nµŠÇ

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„‘š¸É°¥¼nĜ¦¼ž“µœ‡ªµ¤¦¼o×¥Á¨º°„˜´ªÁ¨º°„­nªœ„µ¦´œš¹„Áž}œÅ¢¨rœµ¤­„»¨ .kb ަ„¦¤‹³­¦oµŠ Å¢¨ r .kb Ž¹ÉŠ­µ¤µ¦™œÎµÅžÄoĜ ´Êœ˜°œ„µ¦®µÁ®˜»Ÿ¨­Îµ®¦´„µ¦Ä®o‡Îµž¦¹„¬µ„´Ÿ¼očo˜n°Åž “µœ‡ªµ¤¦¼o °Š¦³‹³°¥¼nĜ¦¼ž °ŠÅ¢¨r˜´ª°´„¬¦Ž¹ÉŠ¤¸œµ¤­„»¨ .kb ¨³Äo „µ¦Âšœ‡ªµ¤¦¼o„‘ (Rule-based system) Ĝ„µ¦„ε®œ—“µœ‡ªµ¤¦¼o Ÿ¼očo‹³˜o°Š¡·¤¡r‡nµ‡ªµ¤‹¦·Š „‘˜nµŠÇ ¦ª¤š´ÊŠ‡Îµ™µ¤š¸É‹³™µ¤˜n°Ÿ¼očoÄ®o°¥¼nĜ¦¼žÂš¸É„ε®œ— Ž¹ÉŠÃ‡¦Š­¦oµŠ„µ¦„ε®œ— “µœ‡ªµ¤¦¼ož¦³„°—oª¥ 4 ­nªœ ŗo„ n ­nªœ REM čo­Îµ®¦´„µ¦Â­—Š o°‡ªµ¤š¸ÉŤn˜o°Š„µ¦Ä®o­—ŠÄœ –³š¸É ަ„¦¤„ε¨´Šž¦³¤ª¨Ÿ¨ ˜n°µ‹Á ¸¥œ ¹ÊœÁ¡ºÉ°‡ªµ¤Á oµÄ‹ °ŠŸ¼o¡´•œµÁ°Š ­nªœ RULE Áž}œ­nªœ °Š„µ¦„ε®œ—„‘ Ž¹ÉŠ„µ¦„ε®œ—‹³ž¦³„°—oª¥ºÉ°„‘ ­nªœ °Š IF ®¦º°ÁŠºÉ°œÅ ¨³­nªœ Then ®¦º°­nªœ„µ¦„¦³šÎµÁ¤ºÉ°„‘Áž}œ‹¦·Š š´ÊŠ­nªœ °Š IF ¨³ Then ‹³˜o°Š„ε®œ—˜´ªÂž¦ ¨³‡nµ °Š˜´ªÂž¦ ×¥˜´ªÂž¦‹³„ε®œ—£µ¥ÄœÁ‡¦ºÉ°Š®¤µ¥ [] ¨³ ­nªœ‡nµ °Š˜´ªÂž¦‹³„ε®œ—£µ¥ÄœÁ‡¦ºÉ°Š®¤µ¥ ºÉ°˜´ªÂž¦Â¨³‡nµ °Š˜´ªÂž¦œ¸Êŗo¤µ‹µ„­nªœ “” °Š„µ¦„ε®œ—‡Îµ™µ¤ ¨³‡nµ˜´ªÁ¨º°„ °Š‡Îµ™µ¤

­nªœ„µ¦„ε®œ—‡Îµ™µ¤ ¨³‡nµ˜´ªÁ¨º°„ °Š‡Îµ™µ¤ ®¦º°­nªœ PROMPT Áž}œ „µ¦„ε®œ—‡Îµ™µ¤š¸É‹³™µ¤˜n°Ÿ¼očo Ž¹ÉŠÂ˜n¨³‡Îµ™µ¤‹³ž¦³„°—oª¥‡nµ °Š˜´ªÁ¨º°„®¦º°‡nµ‡ªµ¤‹¦·Š

(facts) Á¡ºÉ°Ä®oŸ¼očoÁ¨º°„‡nµ‡ªµ¤‹¦·ŠÁ®¨nµœ´ÊœÁ oµ­¼n¦³ ­nªœ­»—šoµ¥Áž}œ­nªœ„µ¦„ε®œ—Ážjµ®¤µ¥ Ž¹ÉŠ„µ¦®µÁ®˜»Ÿ¨‹³ (GOAL) ­·Êœ­»—¨ŠÁ¤ºÉ°¡„´Ážjµ®¤µ¥ ºÉ° °ŠÁžjµ®¤µ¥­µ¤µ¦™„ 宜—Å—o£µ¥ÄœÁ‡¦ºÉ°Š®¤µ¥ [] „µ¦„ε®œ—“µœ‡ªµ¤¦¼o °Š¦³­µ¤µ¦™Â­—Š˜´ª°¥nµŠÅ—o—´Šœ ¸Ê

REM Test Knowledge Base (weather.kb) RULE [Is it going to rain?] If [precipitation] = "expected" Then [the recommendation] = "wear a raincoat" PROMPT [precipitation] MultiChoice CF "According to the weather forecast, precipitation is:" "expected" "not expected" GOAL [the recommendation]

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£µ¡š ¸É 8 ˜´ª°¥µŠ„µ¦„n 宜—“µœ‡ªµ¤¦¼o °Š¦³ „µ¦®µÁ®˜»Ÿ¨ °Š¦³‹³Äo¦¼žÂ„µ¦®µÁ®˜»Ÿ¨Å—oš´ÊŠÂÁ—·œ®œoµ (Forward-chaining) ¨³„µ¦®µÁ®˜»Ÿ¨Â™°¥®¨´Š (Backward-chaining) Ž¹ÉŠª·›¸„µ¦®µÁ®˜»Ÿ¨œ´Êœ ‹³Äo„µ¦‹´‡¼n˜´ªÂž¦Â¨³‡nµ‡ªµ¤‹¦·Š °Š„‘ „´‡nµ‡ªµ¤‹¦·Šš¸Éŗo¦´¤µ‹µ„Ÿ¼očo ¡¦o°¤„´‡nµ ‡ªµ¤¤´ÉœÄ‹ (CF) Ĝ‡nµ‡ªµ¤‹¦·Šœ´ÊœÇ š¸ÉŸ¼očoÁž}œŸ¼o„ε®œ— ¨³¦³‹³‡Îµœª–®µ‡nµ‡ªµ¤¤´ÉœÄ‹ °°„¤µÄœ¦¼ž °ŠÁž°¦rÁŽÈœ˜rĜ‡Îµ˜°š¸Éŗo‹µ„„µ¦­¦»žŸ¨ ­nªœ„µ¦˜·—˜n°„´Ÿ¼očonŠÁž}œ 2 ¤»¤¤°Š ‡º° ¤»¤¤°Š °ŠŸ¼o¡´•œµ¦³ ¨³ ¤»¤¤°Š °ŠŸ¼očoš´ÉªÅž Ž¹ÉŠ¤µ °‡Îµž¦¹„¬µ‹µ„¦³ Ĝ¤»¤¤°Š °ŠŸ¼o¡´•œµ¦³œ´Êœ­µ¤µ¦™ „ε®œ—“µœ‡ªµ¤¦¼o Á¡·É¤ ¨ „oÅ „‘Å—o ¨³˜¦ª‹­°„µ¦®µÁ®˜»Ÿ¨Å—o×¥Ážd—„µ¦˜¦ª‹­° ‡ªµ¤Ÿ·—¡¨µ— (Debug) ˜nĜ­nªœ °ŠŸ¼očo¦³š´ÉªÅž‹³Å¤n­µ¤µ¦™‹´—„µ¦­nªœ“µœ‡ªµ¤¦¼oŗo Ž¹ÉŠ ­µ¤µ¦™ÄoŗoÁ¡¸¥Šžj°œ‡nµ‡ªµ¤‹¦·ŠÁ oµ­¼n¦³ ¨³Á¦¸¥„—¼Ÿ¨¨´¡›rĜ„µ¦­¦»žŸ¨Ÿnµœ‡Îµ­´ÉŠ Why ®¦º°š¸ÉÁ¦¸¥„ªnµ 1.7.4 The Java Expert System Shell (Friedman-Hill 2003) JESS Áž}œÃ‡¦Š¦nµŠ¦³Ÿ¼oÁ¸É¥ªµŽ¹ÉŠÄo£µ¬µ‹µªµ (JAVA) Ĝ„µ¦¡´•œµ ×¥¤¸¡ºÊœ“µœÃž¦Â„¦¤¤µ

‹µ„£µ¬µ CLIPS (C Language integrated production System) Ž¹ÉŠÁž}œš¸ÉčoĜ„µ¦¡´•œµ¦³ Ÿ¼oÁ¸É¥ªµÃ—¥ÁŒ¡µ³

JESS ­œ´­œ»œ„µ¦­¦oµŠ¦³Ÿ¼oÁ¸É¥ªµš¸É¤¸„µ¦Âšœ‡ªµ¤¦¼o„‘ (Rule- ¨³Äo„µ¦®µÁ®˜»Ÿ¨Â„‘ —oª¥ª·›¸„µ¦®µÁ®˜»Ÿ¨Â¥o°œ„¨´ based expert system) (Backward chaining) Ž¹ÉŠ„¦³ªœ„µ¦œ¸Ê¡´•œµÃ—¥Ä o°´¨„°¦·š¹¤­Îµ®¦´„µ¦‹´‡¼n¦¼žÂš¸ÉÁ¦¸¥„ªnµ Rete algorithm o°—¸ °Š°´¨„°¦·š¹¤œ¸Ê‡º° ­µ¤µ¦™®µÁ®˜»Ÿ¨Äœž{®µ¥µ„Ç ŗo°¥nµŠ¤¸ž¦³­·š›·£µ¡ ˜´ª°¥nµŠ„µ¦Âšœ‡ªµ¤¦¼o °Š JESS Ž¹ÉŠ¤¸®¨´„„µ¦ÄoŠµœÁ®¤º°œ„´£µ¬µ CLIPS —´Šœ ¸Ê

(defrule IDDM (Patient (name ?first ?last)(age ?age)) (test (< ?age 30)) (BPressure Hypotension) (Symptoms (ketonuria yes)) (exists (or(Symptoms(coma yes)) (Symptoms(CrackedLips yes)) (Symptoms(Tachycardia yes)) (Symptoms(Confusion yes) (Symptoms(polyuria yes) (polydipsia yes) (polyphygia yes))))) => (assert(Type(type IDDM))) (printout t ?first” “?last “Has Diabetes type 1” crlf))

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£µ¡š ¸É 9 ˜´ª°¥nµŠ„µ¦Âšœ‡ªµ¤¦¼o °Š JESS ˜´ª°¥nµŠ oµŠ˜oœÁž}œ„µ¦­¦oµŠ„‘Äœ„µ¦˜¦ª‹­°Ã¦‡Áµ®ªµœ œ·—¡¹ÉŠ °·œŽ¼¨·œ (insulin dependent diabetes mellitus, IDDM) ץčo‡Îµªnµ defrule Áž}œ‡Îµ­Šªœš¸É­—Šªnµ Áž}œ„µ¦„ε®œ—„‘ ­nªœ °Š„‘¤¸­°Š­nªœ ‡´Éœ—oª¥Á‡¦ºÉ°Š®¤µ¥ “=>” ×¥­nªœÂ¦„„n°œÁ‡¦ºÉ°Š®¤µ¥ “=>” Áž}œ­nªœÁŠºÉ°œÅ ¨³­nªœš¸É­°Š®¨´ŠÁ‡¦ºÉ°Š®¤µ¥ “ =>” Áž}œ­nªœš¸É„ε®œ—„µ¦„¦³šÎµ ®¦º° o°­¦»ž °Š„‘ o°—¸ °Š JESS š¸ÉחÁ—nœ‡º°­µ¤µ¦™šÎµŠµœÂ‡Îµ­´ÉŠ­‡¦·ž Ž¹ÉŠ­nŠŸ¨Ä®oŸ¼očo ­µ¤µ¦™­¦oµŠª´˜™» (Object) Á¡ºÉ°Á¦¸¥„čo¦³Á¸¥ª·›¸ (Method) ˜nµŠÇ ŗo×¥˜¦Š œ°„‹µ„œ¸Ê¥´Š ­µ¤µ¦™­¦oµŠ­nªœ˜·—˜n°Ÿ¼očoŗoץŤn˜o°ŠÂž¨Ãž¦Â„¦¤ (Compile) £µ¬µ‹µªµ°¸„—oª¥ ªŠ‹¦„µ¦ž¦³¤ª¨Ÿ¨ °ŠÃ‡¦Š¦nµŠ¦³Ÿ¼oÁ¸É¥ªµ JESS ž¦³„°—oª¥ 3 ´Êœ˜°œ—oª¥„´œ —´Šœ ¸Ê Áž¦¸¥Áš¸¥‡nµ‡ªµ¤‹¦·Šš¸É¤¸°¥¼n„´‡ªµ¤‹¦·ŠÄœ“µœ‡ªµ¤¦¼oš¸É™¼„šœ°¥¼nĜ 1. ¦¼ž °Š„‘ Ž¹ÉŠÁž}œ‡nµš¸É°¥¼n {~ŠŽoµ¥¤º° °Š„‘ ®¦º°­nªœ °ŠÁŠºÉ°œÅ ®µ„‡nµ‡ªµ¤‹¦·Š­°—‡¨o°Š„´„‘

¦³‹³šÎµ„µ¦Á¨º°„„‘ o°œœÅžž¦³¤ª¨Ÿ¨´Ê 2. Á¦¸¥Š¨Îµ—´„‘ ¨³„ε‹´—‡ªµ¤ ´—Â¥oŠ„´œ °Š„‘ o°˜nµŠÇ Ž¹ÉŠ‹³Å—o„‘š¸É

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˜oœÅ¤o˜´—­·œÄ‹¤¸¨´„¬–³‡¨oµ¥Ã‡¦Š­¦oµŠ˜oœÅ¤o š¸Éž¦³„°—oª¥‹»—˜n°£µ¥Äœ (internal node) ®¦º°Áž}œ‹»—˜n°š¸ÉčoĜ„µ¦˜´—­·œÄ‹ ÁºÉ°¤˜n°—oª¥„·ÉŠ °Š˜oœÅ¤oŽ¹ÉŠœÎµÅž­¼nŸ¨¨´¡›rš¸É ŗo‹µ„„µ¦š—­° ¨³­nªœ¨nµŠ­»— °Š˜oœÅ¤o‡º°Ä Ž¹ÉŠÁž}œŸ¨¨´¡›r­»—šoµ¥š¸ÉŤn­µ¤µ¦™Â˜„„·ÉŠ °°„Şŗo°¸„ ®¦º°Áž}œœ·— °Š„¨»n¤˜nµŠÇ °Š o°¤¼¨ ­nªœ‹»—œ­»— °ŠÃ‡¦Š­¦oµŠ˜oœÅ¤oÁ¦¸¥„ªnµ‹»— ˜n°š¸ÉÁž}œ¦µ„ (root node) Ž¹ÉŠÁž}œ‹»—Á¦·É¤˜oœ °Š„µ¦­¦oµŠ˜oœÅ¤ o (Han and Kamber 2007 : 291) „µ¦Äo˜oœÅ¤o˜´—­·œÄ‹­µ¤µ¦™œÎµÅžž¦³¥»„˜rčoĜ„µ¦‹ÎµÂœ„ž¦³Á£š o°¤¼¨®¨µ¥ —oµœ Ánœ „µ¦šÎµ˜¨µ—¨¼„‡oµ„¨»n¤Ážjµ®¤µ¥ „µ¦°œ»¤´˜·‡Îµ °¤¸´˜¦Á‡¦—·˜ ®¦º°„µ¦ª·œ·‹Œ´¥šµŠ „µ¦Â¡š¥ r 1.8.1 ´Êœ˜°œ„µ¦‹ÎµÂœ„ž¦³Á£š o°¤¼¨ ž¦³„°—oª¥ 2 ´Êœ˜°œ ‡º° ´Êœ˜°œ„µ¦ ­¦oµŠÂ‹Îµ¨°Š ¨³ ´Êœ˜°œ„µ¦œÎµÂ‹Îµ¨°ŠÅžÄo ×¥ ´Êœ˜°œ„µ¦­¦oµŠÂ‹Îµ¨°Š ‹³ÄoÁŽ˜ o°¤¼¨˜´ª°¥nµŠ®¦º°Á¦¸¥„ªnµ»— o°¤¼¨­°œ (training set) Ĝ„µ¦Á¦¸¥œ¦¼oÁ¡ºÉ°­¦oµŠÂ‹Îµ¨°Š ×¥œÎµ»— o°¤¼¨­°œÁ®¨nµœ¸Êު·Á‡¦µ³®r—oª¥ ´Êœ˜°œª·›¸ °Š„µ¦‹ÎµÂœ„ž¦³Á£š˜nµŠÇ Ž¹ÉŠŸ¨¨´¡›r­µ¤µ¦™

ž¨ŠÄ®o°¥¼nĜ¦¼žÂ °Š„‘ ‹µ„œ´ÊœÄœ ´Êœ˜°œ„µ¦œÎµÂ‹Îµ¨°ŠÅžÄ o ‹³˜o°ŠšÎµ„µ¦ž¦³¤µ–‡nµ

‡ªµ¤Â¤nœ¥Îµ (accuracy) „n°œœÎµÅžÄo ×¥Áž¦¸¥Áš¸¥Ÿ¨„µ¦‹ÎµÂœ„ž¦³Á£š °Šž¦³Á£š„¨»n¤ o°¤¼¨š¸Éš¦µ¨nªŠ®œoµ „´„µ¦‹ÎµÂœ„ž¦³Á£šÃ—¥Äo‹Îµ¨°Š ‡nµ‡ªµ¤™¼„˜o°Šš¸Éŗoª´—‹µ„

Áž°¦rÁŽÈœ˜r‡ªµ¤™¼„˜o°Š °ŠÂ‹Îµ¨°Šš¸É­¦oµŠ ¹Êœ ®µ„‡nµ‡ªµ¤Â¤nœ¥Îµ°¥¼nĜÁ„–”rš¸É­µ¤µ¦™ ¥°¤¦´Å—o ‹¹Š‹³œÎµÂ‹Îµ¨°ŠÅžÄoĜ„µ¦‹ÎµÂœ„ž¦³Á£š o°¤¼¨Å—o‹¦·Š (Han and Kamber 2007 : 287) 1.8.2 „µ¦Á˜¦¸¥¤ o°¤¼¨ „n°œ„µ¦œÎµÅžÄoĜ„µ¦­¦oµŠÂ‹Îµ¨°Š‹³nª¥ž¦´ž¦»Š‡nµ ‡ªµ¤Â¤nœ¥Îµ ®¦º°ž¦³­·š›·£µ¡ °Š„¦³ªœ„µ¦‹ÎµÂœ„ž¦³Á£š o°¤¼¨Å—o Ž¹ÉŠ„µ¦Á˜¦¸¥¤ o°¤¼¨ ž¦³„°—oª¥ „µ¦šÎµ‡ªµ¤­³°µ— o°¤¼¨ (Data cleaning) „µ¦ª·Á‡¦µ³®r‡ªµ¤Á„¸É¥ª o°Š °Š o°¤¼¨ (Relevance analysis) ¨³„µ¦Âž¨Š o°¤¼¨ (Data transformation) (Han and Kamber 2007 : 289) ´Êœ˜°œ„µ¦šÎµ‡ªµ¤­³°µ— o°¤¼¨ (Data cleaning) „¦³šÎµÁ¡ºÉ°„ε‹´—®¦º°¨— o°¤¼¨¦„ªœ (noise) ¨³Â„oÅ ‡nµ o°¤¼¨š¸É­¼®µ¥ (missing values) ™¹ŠÂ¤oªnµ ´Êœ˜°œª·›¸ °Š „µ¦‹ÎµÂœ„ž¦³Á£š o°¤¼¨­nªœÄ®n¤¸­nªœÄœ„µ¦‹´—„µ¦ o°¤¼¨¦„ªœÂ¨³ o°¤¼¨š¸É­¼®µ¥Â¨oª ˜n „µ¦„¦³šÎµÄœ ´Êœ˜°œœ¸Ê„n°œÄœÁºÊ°Š˜oœ‹³nª¥Ä®o­µ¤µ¦™¨—‡ªµ¤­´­œ °Š‹o°¤¼¨Äœ¦³®ªnµŠ „µ¦Á¦¸¥œ¦¼oŗ o ´Êœ˜°œ„µ¦ª·Á‡¦µ³®r‡ªµ¤Á„¸É¥ª o°Š °Š o°¤¼¨ (Relevance analysis) Ĝ o°¤¼¨ š¸É¤¸‡»–¨´„¬–³ž¦³‹Îµ (attibute) ‹Îµœªœ¤µ„ °µ‹Á„·—‡ªµ¤ŽÊεŽo°œ °Š o°¤¼¨Å—o —´Šœ´Êœ‹¹Š˜o°Š„ε‹´— ‡ªµ¤ŽÊεŽo°œ—oª¥„µ¦ª·Á‡¦µ³®r‡nµ­®­´¤¡´œ›r (Correlation analysis) Ž¹ÉŠÁž}œ­™·˜·š¸Éčo®µ‡ªµ¤­´¤¡´œ›r

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¦³®ªnµŠ˜´ªÂž¦ ®¦º°®µ„ o°¤¼¨š¸ÉÁ„ȝ°¥¼nĜ¦¼ž °Š“µœ o°¤¼¨Ž¹ÉŠ¤¸‡»–¨´„¬–³ž¦³‹Îµ š¸ÉŤnÁ„¸É¥ª o°Š „´œ °µ‹Äoª·›¸„µ¦Á¨º°„ÁŒ¡µ³µŠ‡»–¨´„¬–³ (Attribute subset selection) š¸É¤¸‡ªµ¤Á„¸É¥ª o°Š„´ Ÿ¨¨´¡›r„µ¦šÎµœµ¥ °¥nµŠÅ¦„Șµ¤š´ÊŠ­°Šª·›¸œ¸ÊÁž}œ„µ¦‡oœ®µ‡»–¨´„¬–³ž¦³‹Îµš¸ÉŤn¤¸Ÿ¨˜n°„¦³ªœ„µ¦ ‹ÎµÂœ„ž¦³Á£š o°¤¼¨ Ž¹ÉŠ‡»–¨´„¬–³ž¦³‹ÎµÁ®¨nµœ´Êœ°µ‹šÎµÄ®oÁ„·—‡ªµ¤¨nµoµÄœ„µ¦ž¦³¤ª¨Ÿ¨ ®¦º°°µ‹šÎµÄ®oÁ„·—Ÿ¨¨´¡›rš¸É·—Áº°œÅžÄœ ´Êœ˜°œ„µ¦Á¦¸¥œ¦ ¼o (Han and Kamber 2007 : 289) „µ¦Âž¨Š o°¤¼¨ (Data transformation) —oª¥ª·›¸„µ¦šÎµ o°¤¼¨Ä®oÁž}œ¤µ˜¦“µœ (Normalization) ×¥„µ¦šÎµÄ®o‡nµ„µ¦„¦³‹µ¥ o°¤¼¨Ä®o°¥¼nĜnªŠ­´ÊœÇ Ánœ ĜnªŠ -1.0 ™¹Š 1.0 ®¦º° nªŠ 0.0 ™¹Š 1.0 ®¦º°„µ¦Âž¨Š‡nµ˜´ªÁ¨ Ä®oÁž}œ‡nµÅ¤n˜n°ÁœºÉ°Š Ánœ ž¨Š‡nµ¦µ¥Å—oŽ¹ÉŠÁž}œ˜´ªÁ¨ Ä®o °¥¼nĜ 3 nªŠ ‡º° ˜Éε žµœ„¨µŠ ­¼Š Áž}œ˜oœ (Han and Kamber 2007 : 290) 1.8.3 ´Êœ˜°œª·›¸ (Algorithm) ­Îµ®¦´„µ¦‹ÎµÂœ„ž¦³Á£š o°¤¼¨—oª¥Ã‡¦Š­¦oµŠ ˜oœÅ¤ o ¤¸®¨µ¥ ´Êœ˜°œª·›¸ ŗ„o n ID3, C4.5 ¨³ CART ĜnªŠž¨µ¥že‡¦·­˜r«´„¦µ ™¹Š˜oœže œ´„ª·‹´¥—oµœ 1970 1980 J.Ross Quinlan „µ¦Á¦¸¥œ¦¼o °ŠÁ‡¦ºÉ°Š‹´„¦ (machine learning) ŗo¡´•œµ ´Êœ˜°œª·›¸Ã‡¦Š­¦oµŠ˜oœÅ¤oš¸É¦¼o‹´„„´œÄœºÉ°

ID3 (Iterative Dichotomiser) ×¥¤¸¡ºÊœ“µœ¤µ‹µ„Áš‡œ·‡„µ¦ÂnŠÁ¡ºÉ°Á°µœ³ (Divide-and-conquer algorithm) ×¥„µ¦ÂnŠ o°¤¼¨Áž}œ­nªœ¥n°¥Ç ¨oª‹¹Š‹³šÎµ„µ¦Â„ož{®µÄœ­nªœ¥n°¥Ç œ´Êœ „n°œ‹³

Á°µš»„­nªœ¤µ¦ª¤„´œ ®¦º°š¸ÉÁ¦¸¥„ªnµ „µ¦ªœŽÊ坝œ¨Š¨nµŠ (Top-Down Recursive) ×¥‹³Á¦·É¤ ‹µ„„µ¦Á¨º°„¨´„¬–³ž¦³‹Îµš¸É—¸š¸É­»—¤µÁž}œ‹»—¦µ„ ‹µ„œ´Êœ‹¹Š®µ¨´„¬–³ž¦³‹Îµš¸É—¸š¸É­»—¤µÁžœ‹} —˜» n°

£µ¥Äœ °ŠÂ˜n¨³„·ÉŠ˜n°ÅžŽ¹ÉŠ„µ¦­¦oµŠ‹ »—˜n°£µ¥Äœ‹³šÎµÄœ¨´„¬–³ªœŽÊε ‹œ o°¤¼¨š¸ÉŸnµœ„µ¦ nŠÂ¥„œ´Êœ‹³‹´—°¥¼nĜ„¨»n¤Á—¸¥ª„´œ ®¦º°‹Îµœªœ o°¤¼¨š¸ÉŸnµœÄœÂ˜n¨³„·ÉŠ¤¸‡nµœo°¥„ªnµš¸É„ε®œ—Ū o „µ¦­¦oµŠ˜oœÅ¤oץčo®¨´„„µ¦ªœŽÊ坝œ¨Š¨nµŠ‹³œÎµÅžÄo„´ o°¤¼¨š¸É¨´„¬–³ž¦³‹Îµš¸ÉÁž}œ‡nµ Ťn˜n°ÁœºÉ°ŠÁšnµœ´Êœ (Han and Kamber 2007 : 292) ˜n°¤µ J.Ross Quinlan ŗo¡´•œµ ´Êœ˜°œª·›¸ ID3 ¤µÁž}œ C4.5 ×¥ž¦´ž¦»ŠÄ®o ¤¸‡ªµ¤­µ¤µ¦™¤µ„ ¹ÊœÄœ­nªœ„µ¦„´ o°¤¼¨˜´ªÁ¨ o°¤¼¨š¸É­¼®µ¥Åž ¨³„µ¦˜´—„·ÉŠ˜oœÅ¤ o œ°„‹µ„œ¸Ê¥´ŠÁ¡·É¤„µ¦‡´—Á¨º°„‡»–¨´„¬–³ž¦³‹Îµš¸É‹³ÄoÁž}œ‹»—˜n°—oª¥„µ¦Äo‡nµÁ„œ­µ¦­œÁš« (Gain information) ´Êœ˜°œª·›¸ C4.5 ŗo™¼„œÎµ¤µÁž¦¸¥Áš¸¥„´ ´Êœ˜°œª·›¸ CART (Classification and Regression Trees) Ž¹ÉŠ¡´•œµÃ—¥„¨»n¤œ´„­™·˜· L. Breiman, J. Friedman, R. Olshen ¨³ C. Stone Ž¹ÉŠÁž}œ ´Êœ˜°œª·›¸Äœ¦¼žÂ °Š˜oœÅ¤ošª·£µ‡ (Binary tree) ¨³Å—o°µ«´¥®¨´„„µ¦Á—¸¥ª„´ C4.5 Ĝ „µ¦‹´—„µ¦ o°¤¼¨‡nµ­¼®µ¥ ¦ª¤š´ÊŠ¤¸„µ¦‹´—„µ¦„´ o°¤¼¨Å—o®¨µ¥œ·— Ánœ o°¤¼¨š«œ·¥¤ o°¤¼¨ ˜´ªÁ¨ ‹Îµœªœ‹¦·Š ¨³‡nµš¸ÉŤnčn˜´ªÁ¨ (Han and Kamber 2007 : 292)

29

1.8.4 „µ¦‡´—Á¨º°„¨´„¬–³ž¦³‹ÎµÁ¡ºÉ°‹ÎµÂœ„ž¦³Á£š o°¤¼¨ (Han and Kamber 2007 : 296) Áž}œª·›¸„µ¦‡´—Á¨º°„¨´„¬–³ž¦³‹Îµš¸É­µ¤µ¦™ÂnŠ„¨»n¤ o°¤¼¨Å—o—¸š¸É­»— Á¡ºÉ°œÎµ¨´„¬–³ž¦³‹Îµ œ´Êœ¤µÄoÁž}œ‹»—¦µ„ ®¦º°‹»—˜n°£µ¥ÄœÄœ„·ÉŠ °Š˜oœÅ¤ o Á„–”rš¸ÉčoĜ„µ¦Á¨º°„¨´„¬–³ž¦³‹µ‡Î °„µ¦º ‡Îµœª–‡nµÁ„œ (gain) Ž¹ÉŠ‹³šÎµ„µ¦‡Îµœª–Äœš»„¨´„¬–³ž¦³‹Îµ ®µ„¨´„¬–³Ä—š¸É¤¸‡nµÁ„œ­¼Š­»— ­—Šªnµ¨´„¬–³œ´Êœ¤¸‡ªµ¤­µ¤µ¦™Äœ„µ¦‹ÎµÂœ„Å—o­¼Š­»— ‹¹Š‹³Á¨º°„¨´„¬–³ž¦³‹Îµœ´Êœ¤µÁž}œ ‹»—¦µ„ ®¦º°‹»—˜n°£µ¥Äœ Ž¹ÉŠÁ„–”rš¸Éčo‡´—Á¨º°„š¸ÉÁž}œš¸Éœ·¥¤ ŗo„n ‡nµÁ„œ­µ¦­œÁš« (Information gain), ‡nµ­´—­nªœÁ„œ (Gain ratio) ¨³ ‡nµ—´œ¸‹¸œ¸ (Gini index) ‡nµÁ„œ­µ¦­œÁš« (Information gain) čoĜ ´Êœ˜°œª·›¸ ID3 (Han and Kamber 2007 : 297) ‡nµÁ„œœ¸Ê‡Îµœª–Å—oץčo‡ªµ¤¦¼o‹µ„š§¬‘¸­µ¦­œÁš« (information theory) ×¥ ‡nµ­µ¦­œÁš«‹³ ¹Êœ°¥¼n„´‡ªµ¤œnµ‹³Áž}œ °Š o°¤¼¨ Ž¹ÉŠ¤¸®œnª¥ª´—Áž}œ·˜ (bits) ž¦·¤µ– o°¤¼¨š¸É ˜o°Š„µ¦­Îµ®¦´‹ÎµÂœ„ o°¤¼¨Áž}œ„¨»n¤®µÅ—o×¥

m

Info(D) = - 6 pi log2 (pi) (2.1) i =1

‹µ„­¤„µ¦š ¸É 2.1 ‡º° »— °Š o°¤¼¨Äœ¦¼žÂÂ™ªš´ÊŠ®¤— š¸ÉœÎµ¤µ¡·‹µ¦–µ D (record) p ‡º° ‡ªµ¤œnµ‹³Áž}œ °Š»— o°¤¼¨Â™ª D š¸É‹³Áž}œ °Š‡¨µ­ C Ž¹ÉŠ‡Îµœª– i i ×¥ |Ci , D | / |D| m ‡º° ‹Îµœªœ„¨»n¤š´ÊŠ®¤—š¸É˜nµŠ„´œ °Š o°¤¼¨»—œ´Êœ Info(D) ‡º° ‡nµÁŒ¨¸É¥¦ª¤ °Š­µ¦­œÁš«š¸É­µ¤µ¦™¦³»‡¨µ­ °Š»— o°¤¼¨Äœ ™ª D ŗ o ®¦°šº ¸É¦¼o‹´„„´œªnµÁž}œ‡nµ‡ªµ¤Å¤Ážn }œ¦³Á¥¸ (Entropy) °Š D ‡nµ‡ªµ¤Å¤nÁž}œ¦³Á¸¥ (Entropy) °Š¨´„¬–³ž¦³‹Îµ (attribute) A Ž¹ÉŠ¤¸‡nµ

Áž}œ (a123 , a , a ,…….., a v ) ®µÅ—o×¥

v |Dj| InfoA(D) = 6 ¯ Info(Dj ) (2.2) j =1 |D|

‹µ„­¤„µ¦š ¸É 2.2 A ‡º° ¨´„¬–³ž¦³‹Îµ A v ‡º° „¨»n¤¥n°¥ °Š¨´„¬–³ž¦³‹Îµ A

|Dj | ‡º° ­¤µ·„ °Š¨´„¬–³ž¦³‹Îµ A š¸É¤¸‡nµ v

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|D| ‡º° »— °Š o°¤¼¨Äœ¦¼žÂÂ™ªš´ÊŠ®¤— (record) š¸ÉœÎµ¤µ¡·‹µ¦–µ

Info(Dj) ‡º° ‡nµ‡ªµ¤Å¤nÁž}œ¦³Á¸¥ (Entropy) °Š Dj

InfoA(D) ‡º° ‡nµ‡ªµ¤Å¤nÁž}œ¦³Á¸¥ (Entropy) °Š¨´„¬–³ž¦³‹Îµ A ‡nµÁ„œ­µ¦­œÁš«Ž¹ÉŠÄo¡·‹µ¦–µÁ¨º°„¨´„¬–³ž¦³‹Îµ¤µÁž}œ‹»—¦µ„ ®¦º°‹»—˜n° £µ¥ÄœÃ‡¦Š­¦oµŠ˜oœÅ¤o¤¸‡nµÁšnµ„´ž¦·¤µ– °Š o°¤¼¨š¸É˜o°Š„µ¦­Îµ®¦´„µ¦‹ÎµÂœ„„¨»n¤ °Š o°¤¼¨ ¨—oª¥ž¦·¤µ– o°¤¼¨š¸É˜o°Š„µ¦­Îµ®¦´‹ÎµÂœ„„¨»n¤ °Š o°¤¼¨Ã—¥Äo¨´„¬–³ž¦³‹Îµ A Á ¸¥œÁž}œ ­¤„µ¦Å—o—´Šœ ¸Ê

Gain(A) = Info(D) - InfoA(D) (2.3)

‹µ„­¤„µ¦š ¸É 2.3 Gain(A) Áž}œ‡nµš¸É°„™¹Šž¦·¤µ– o°¤¼¨š¸É˜o°Š„µ¦®µ„čo¨´„¬–³ž¦³‹Îµ A

Áž}œ˜´ª˜¦ª‹­°Á¡ºÉ°‹ÎµÂœ„„¨»n¤ o°¤¼¨ ‡nµÁ„œ­µ¦­œÁš«¥´Š¤¸‡ªµ¤¨ÎµÁ°¸¥Š°¥nµŠ¤µ„ Ĝ„µ¦Á¨º°„¨´„¬–³ž¦³‹Îµš¸É¤¸

‡nµš¸ÉÁž}œÅžÅ—o‹Îµœªœ¤µ„Ç ¨³ÄœÂ˜n¨³˜´ª°¥nµŠ¤¸‡nµÅ¤nŽÊε„´œ Ž¹ÉŠ‹³šÎµÄ®oŗo‡nµÁ„œ­µ¦­œÁš«¤¸ ‡nµ­¼Š„ªnµ¨´„¬–³ž¦³‹Îµ°ºÉœ ‹¹ŠšÎµÄ®o¨´„¬–³ž¦³‹Îµœ¸Ê™¼„Á¨º°„ —´Šœ´ÊœÄœ ´Êœ˜°œª·›¸ C4.5 ‹¹Š¤¸„µ¦Äo

‡nµ¤µ˜¦“µœ°´˜¦µ­nªœÁ„œ (Gain ratio criterion) ¤µÄoÁ¡ºÉ°ž¦´‡nµÁ„œÄ®o™¼„˜o°Š (Han and Kamber

2007 : 301) ץčo‡nµ­µ¦­œÁš«„µ¦ÂnŠÂ¥„ (split information) °ŠÂ˜n¨³¨´„¬–³ž¦³‹ÎµÁ¡ºÉ° œÎµ¤µÄo‡Îµœª–‡nµÁ„œ­µ¦­œÁš« ­µ¤µ¦™‡ 圪–Å—o—´Šœ ¸Ê

v |Dj| SplitInfoA(D) = 6 ¯ log2 |D j| (2.4) j =1 |D| |D|

¨³‡nµ¤µ˜¦“µœ°´˜¦µ­nªœÁ„œ­µ¤µ¦™‡Îµœª–Å—o—´Šœ ¸Ê

GainRatio(A) = Gain(A) (2.5) SplitInfo(A)

1.8.5 „µ¦˜´—„·ÉŠ˜oœÅ¤o˜´—­·œÄ‹ (Han and Kamber 2007 : 304) Áž}œ„µ¦nª¥Â„ož{®µ ‡ªµ¤¡°—¸Á„·œÅž °Š o°¤¼¨ (overfitting) Ž¹ÉŠÁ„·— ¹ÊœÄœ„µ¦­¦oµŠÂ‹Îµ¨°Šš¸É­µ¤µ¦™Äo‹ÎµÂœ„ o°¤¼¨ ­°œÅ—oÁšnµœ´Êœ ˜nŤn­µ¤µ¦™œÎµ¤µÄoĜ„µ¦‹ÎµÂœ„ o°¤¼¨Ä®¤nŗo Ž¹ÉŠ„µ¦˜´—„·ÉŠ˜oœÅ¤o˜´—­·œÄ‹ nŠÁž}œ­°Šž¦³Á£šÄ®nÇ ‡º° „µ¦˜´—„·ÉŠ –³Á¦¸¥œ¦¼o (pre-pruning) ¨³„µ¦˜´—„·ÉŠÅ¤o®¨´Š„µ¦ Á¦¸¥œ¦ ¼o (post-pruning) „µ¦˜´—„·ÉŠ –³Á¦¸¥œ¦¼o (pre-pruning) ‹³šÎµÄœ¦³®ªnµŠ„µ¦­¦oµŠ˜oœÅ¤o×¥‡Îµœª–

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‡nµ‡ªµ¤Ÿ·—¡¨µ—š¸É‹³Á„·— ¹Êœ °Š‹»—˜n°£µ¥Äœš¸É„ε¨´Š­¦oµŠ ¹Êœ ®µ„‹»—œ´ÊœšÎµÄ®oÁ„·—‡ªµ¤Ÿ·—¡¨µ— Ĝ„µ¦‹ÎµÂœ„ž¦³Á£š­¼Š„ªnµ„µ¦Å¤nčo‹»—œ ¸Ê „È‹³Å¤n­¦oµŠ‹»—˜n°£µ¥Äœœ¸Ê¨³˜´—˜oœÅ¤o¥n°¥ °Š‹»—˜n°œ¸Ê °°„Åž „µ¦˜´—„·ÉŠÅ¤o®¨´Š„µ¦Á¦¸¥œ¦¼o (post-pruning) ‹³šÎµÁ¤ºÉ°¤¸„µ¦­¦oµŠ˜oœÅ¤oÁ­¦È‹Â¨oª Ž¹ÉŠÄoĜ ´Êœ˜°œª·›¸ C4.5 ×¥¤¸ 2 ª·›¸š¸É­Îµ‡´ ŗo„n „µ¦˜´—„·ÉŠÂ‡ªµ¤Ÿ·—¡¨µ—¨—¨Š (Reduced- error pruning) ¨³„µ¦˜´—„·ÉŠÃ—¥Äo‡nµ‡ªµ¤Ÿ·—¡¨µ— (Error-based pruning) ×¥„µ¦˜´—„·ÉŠÂ ‡ªµ¤Ÿ·—¡¨µ—¨—¨Š (Reduced-error pruning) ˜o°ŠÄo»— o°¤¼¨˜´—„·ÉŠÂ¥„°°„‹µ„»— o°¤¼¨ f„ ´Êœ˜°œ„µ¦šÎµŠµœ‹³®µ‡ªµ¤Ÿ·—¡¨µ—Äœ„µ¦‹ÎµÂœ„ o°¤¼¨ °Š„·ÉŠÅ¤o˜n¨³„·ÉŠ ®µ„„·ÉŠ¨¼„ °Š‹»—˜n°Ä— ¤¸‡ªµ¤Ÿ·—¡¨µ—¤µ„„ªnµ„µ¦Áž¨¸É¥œ‹»—œ´ÊœÁž}œÄ „È‹³˜´—„·ÉŠ¨¼„œ´Êœ°°„¨oªÁž¨¸É¥œÁž}œÄÂšœ Ž¹ÉŠ ‹³„¦³šÎµªœŽÊε‹µ„¨nµŠ ¹ÊœœÃ‡¦Š­¦oµŠ˜oœÅ¤ o ‹œ„ªnµ‹³Å¤ n ­µ¤µ¦™˜´—„·ÉŠÅ—o°¸„ ­nªœ„µ¦˜´—„·ÉŠÃ—¥Äo‡nµ‡ªµ¤Ÿ·—¡¨µ— (Error-based pruning) Á®¤µ³„´„µ¦­¦oµŠ ˜oœÅ¤o‹µ„ o°¤¼¨‹ÎµœªœÅ¤n¤µ„ ÁœºÉ°Š‹µ„‹³Äo o°¤¼¨ f„»—Á—¸¥ª„´ o°¤¼¨š¸Éčo˜´—„·ÉŠ˜oœÅ¤o ª·›¸„µ¦

˜´—„·ÉŠ‹³Á¦·É¤‹µ„­nªœÄ œÅž¥¹Ê ´Š¦µ„ °Š˜œÅ¤o o ×¥‹³‡Îµœª–‡nµ˜ª°¥´ nµŠš¸É‡µ—ªnµ‹³šÎµœµ¥Ÿ·— °Š

„·ÉŠ¥n°¥š¸É˜o°Š„µ¦˜´— ®µ„¦ª¤Â¨oª‡nµ‡ªµ¤Ÿ·—¡¨µ—œo°¥„ªnµ‹¹Š‹³˜—„´ ŠÅ—·É o

2. ‡ªµ¤¦¼oÁ„¸É¥ª„´„µ¦‹ÎµÂœ„®°¥œÊε‹º—ªŠ«r Thiaridae ®°¥œÊε‹º—ªŠ«r ‹´—°¥¼nĜި´¤¤°¨¨­„µ´ ´ÊœÂ„­Ãš¦Ã¡¦—µ Thiaridae (Phylum Mollusca) (Class Gastropoda) ´Êœ¥n°¥Ã¡¦ÃŽÂ¦ŠÁ‡ ¸¥ (Subclass Prosobranchia) °´œ—´ Á¤ÃŽÂ„­Ãš¦Ã¡—µ

(Order Mesogastropoda) (ª·ª·»˜µ Á—¦´„¬µ 2549 : 13) ¨´„¬–³Ã—¥š´ÉªÅž °Š®°¥œÊε‹º—ªŠ«r Thiaridae Áž¨º°„‹³¤¸¦¼ž¦nµŠš¦Š„¦ª¥¥µª®¦º° š¦Š„¦ª¥¦¼žÅ n Ÿ·ªÁž¨º°„ŤnÁ¦¸¥ °µ‹Áž}œ­´œ®¦º°°µ‹¤¸¨ª—¨µ¥œ¼œ®¦º° ¦» ¦³ ­Åž¦r¤´„­¹„„¦n°œ ðÁ¡°¦r‡·ª¨´¤ (Operculum) µŠ Áž}œ¤´œ ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) ®¦º°¤´¨˜·­Åž¦´¨ (Multispiral) ®°¥Á¡«Á¤¸¥°°„¨¼„Áž}œ˜´ª (Viviparous) ™»Š˜´ª°n°œ‹³°¥¼nn°ŠÄ˜o¨Îµ˜´ª¦·Áª–‡° ¨³ ¤¸¦¼Ážd—šµŠ—oµœ ªµ °Š‡°Â¨³°µ«´¥°¥¼nĜœÊε‹º— ­nªœÄ®n¡Äœšª¸ž¥»Ã¦ž˜°œÄ˜o °´¢¦·„µ Á°Á¸¥ ¨³°Á¤¦·„µÄ˜ o 2.1 „µ¦‹´—¨Îµ—´´Êœ °Š®°¥œÊε‹—ªŠ«º r Thiaridae ®°¥ÄœªŠ«rœ¸Ê­µ¤µ¦™‹ÎµÂœ„Áž}œ Subfamily ŗo 2 Subfamily ŗo„n Subfamily Thiarinae ¨³ Subfamily Melanatriinae ¨³ÂnŠÁž}œ Genus ŗ o 8 Genus Ž¹ÉŠ¤¸¦µ¥¨³Á°¸¥——´Šœ ¸Ê

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2.1.1 Subfamily Thiarinae Áž¨º°„¤¸¦¼ž¦nµŠžj°¤ ®¦º°Áž}œš¦Š„¦ª¥¦¼žÅ n ¤¸¨´„¬–³ ­¹„„¦n°œ ®¦°¤º ¸¨´„¬–³‡¨oµ¥ž¨µ¥˜´— ˜´ª®°¥¤¸Ÿ·ª­¸‡n°œ oµŠÁ®¨º°Š ðÁ¡°¦r‡·ª¨´¤(Operculum) Áž}œ¦¼žÅ n ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) nŠÁž}œ 5 ­„»¨ —´Šœ ¸Ê 2.1.1.1 Genus Tarebia Áž¨º°„¤¸¦¼ž¦nµŠÁž}œš¦Š„¦ª¥¦¸¥µª ¤¸¨´„¬–³®œµ Áž}œ­¸Á ¸¥ª®¦°­º ¸œÊ嘵¨ Ÿ·ªÁž¨º°„Áž}œ¤´œ ¨³ž„‡¨»¤—ª¥žo »i¤®¦º°˜»n¤„¨¤Á¨È„Ç (Tubercle) ¤¸ œµ— ¥µªž¦³¤µ– 12 – 44 ¤·¨¨·Á¤˜¦ Áž}œ®°¥š¸É¤¸žµ„Áž¨º°„ªœ ªµ®¦º°ÂÁ—È„Žrš¦´¨ (Dextral) ¤¸ ðÁ¡°¦r‡·ª¨´¤ (Operculum) ¡°Ž·­Åž¦´¨ (Paucispiral) Ĝž¦³Áš«Åš¥¤¸°¥Á¡¼n ¸¥Š 1 Species ‡º° Tarebia granifera 2.1.1.2 Genus Thiara Áž¨º°„¤¸¦¼ž¦nµŠÁž}œš¦Š„¦ª¥ ¦¸¥µª ¤¸°—¸Áª·¦r¨ (Body whorl) œµ—Ä®n ­¸Á ¸¥ª¤³„°„ Ÿ·ªÁž¨º°„¤¸®œµ¤ ¤¸ œµ—¥µªž¦³¤µ– 18 – 32 ¤·¨¨·Á¤˜¦ Áž}œ ®°¥š¸É¤¸žµ„Áž¨º°„Áž}œÂÁ—È„Žrš¦´¨ (Dextral) ¤¸Ã°Á¡°¦r‡·ª¨´¤ (Operculum) Áž}œÂ¡°Ž·­- ަ´¨ Ĝž¦³Áš«Åš¥¡ ‡º° (Paucispiral) 1 Species Thiara scabra 2.1.1.3 Genus Sermyla Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¥µª¦¸ ¤¸°—¸Áª·¦r¨ œµ—Ä® n

¤¸­¸Á ¸¥ª®¦º°­¸œÊ嘵¨ ­nªœ¥°— °ŠÁž¨º°„ (Apex) ¤¸¨´„¬–³„¦n°œ Ÿ·ªÁž¨º°„Áž}œ¤´œÂ¨³¤¸¨´„¬–³ ‡¨oµ¥„´®°¥ Tarebia granifera ˜nÁž¨º°„Ťnž„‡¨»¤—oª¥ž»i¤®¦º°˜»n¤„¨¤ Á¨È„Ç (Tubercle) ¦·Áª–

­nªœ“µœ °ŠÁž¨º°„‹³¤¸Á­oœ spiral ridges Á®ÈœÅ—o°¥nµŠ´—Á‹œ µŠ‡¦´ÊŠ°µ‹¤¸®œµ¤ (spine) ‡¨oµ¥„´ ®°¥ Thiara scabra ×¥š´ÉªÅž¤¸ œµ—¥µªž¦³¤µ– ¤·¨¨·Á¤˜¦ Áž}œ®°¥š¸É¤¸žµ„Áž¨º°„Áž}œ 9 -17 Á—È„Žrš¦´¨ (Dextral) ¤¸Ã°Á¡°¦r‡·ª¨ ´¤ (Operculum) Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) Ĝ ž¦³Áš«Åš¥¡ 1 Species ‡º° Sermyla riqueti 2.1.1.4 Genus Melanoides Áž¨º°„¤¸¦¼ž¦nµŠ¥µª¦¸ ¤¸Áª·¦r¨ž¦³¤µ– 12 – 16 Áª·¦r¨ Ž¹ÉŠ‡n°¥Ç ¤¸ œµ—Ä®n ¹Êœ Áª·¦r¨°µ‹¤¸¨´„¬–³œ¼œ®¦º°Âœ ­nªœ¥°— °ŠÁž¨º°„ (Apex) ¤´„¤¸ ¨´„¬–³„¦n°œ®¦º°¤¸¨´„¬–³‡¨oµ¥ž¨µ¥˜´— (truncate) Áž¨º°„¤¸­¸œÊ嘵¨®¦º°­¸Á ¸¥ª¤³„°„ Ÿ·ªÁž}œ ­´œ ¨³Ÿ·ªÁž¨º°„ž„‡¨»¤—oª¥ž»i¤Á¨È„Ç ¤¸ œµ—¥µªž¦³¤µ– 22 – 42 ¤·¨¨·Á¤˜¦ Áž}œ®°¥š¸É¤¸žµ„Áž¨º°„ Á—È„Žrš¦´¨ (Dextral) ¤¸Ã°Á¡°¦r‡·ª¨´¤Áž}œ¦¼žÅ n¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) Ĝ ž¦³Áš«Åš¥¡ 2 Species ‡º° Melanoides tuberculata ¨³ Melanoides jugicostis 2.1.1.5 Genus Neoradina Áž¨º°„¤¸¦¼ž¦nµŠ¥µª¦¸ ¤¸ œµ—®œµÂ¨³Ä®n ¤¸­¸ Á ¸¥ª¤³„°„ ¤¸Áª·¦r¨ž¦³¤µ– 10 -14 Áª·¦r¨ Áž¨º°„®°¥¥µªž¦³¤µ– 44 – 48 ¤·¨¨·Á¤˜¦ Ÿ·ªÁ¦¸¥®¦º° ¤¸­´œÁž}œÁ„¨¸¥ª ­nªœ¥°— °ŠÁž¨º°„¤¸¨´„¬–³„¦n°œ (Eroded) ®°¥¤¸žµ„Áž¨º°„„ªoµŠ ¦¼žÅ n ¨³ Áž}œÂÁ—È„Žrš¦´¨ (Dextral) ðÁ¡°¦r‡·ª¨´¤ (Operculum) Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) Ĝ ž¦³Áš«Åš¥¡ 1 Species ‡º° Neoradina prasongi

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2.1.2 Subfamily Melanatriinae Áž¨º°„¤¸¦¼ž¦nµŠžj°¤ ®¦º°Áž}œ¦¼žÅ n ×¥š´ÉªÅž Áž¨º°„‹³®œµ ¤¸­¸œÊ嘵¨ ¨´„¬–³ °ŠÁž¨º°„¤¸®¨µ¥ž¦³Á£š °µ‹‹³Á¦¥¸ ®¦º°ÁžœÁ­} oœ ®¦°¤º ¸ ° œ¼œÁž}œ „œ ®¦º°¤¸˜»n¤ ®¦°¤º ¸®œµ¤Â®¨¤ ðÁ¡°¦r‡·ª¨´¤„¨¤ ®¦º°Áž}œ¦¼žÅ n °ÂŸnœÁœºÊ°‡¨¤˜» ´ª (Mantle) Áž}œ˜³Á ȝ (Fringed) ˜´ª®°¥¤¸­¸Ášµ—ε ®¦º°‡n°œ oµŠ—ε ¨³¤¸‹»—­¸Á®¨º°Š®¦º°­¸­o¤ nŠÁž}œ 3 ­„»¨ —´Šœ ¸Ê 2.1.2.1 Genus Adamietta Áž¨º°„¤¸¦¼ž¦nµŠ¥µª¦ ¸ œµ—žµœ„¨µŠ Ÿ·ªÁž¨º°„Á¦¸¥ ¥„ÁªoœÁ­oœ˜µ¤Âœª˜´ÊŠœŸªÁž¨· º°„ °Š®°¥ (Growth line) Áž¨º°„¤¸­¸œÊ嘵¨°°„Á ¸¥ª ¤³„°„ ¤¸ Áª·¦r¨ž¦³¤µ– 12 – 14 Áª·¦r¨ Á¡·É¤ ¹Êœ˜µ¤ œµ—˜´ª ­nªœ¥°— °ŠÁž¨º°„¤´„¤¸¨´„¬–³„¦n°œ(Eroded) ®°¥¤¸žµ„Áž¨º°„„ªoµŠ¦¼žÅ n ¨³Áž}œÂÁ—È„Žrš¦´¨(Dextral) ðÁ¡°¦r‡·ª¨´¤ (Operculum) Áž}œ ¡°Ž·­Åž¦´¨ (Paucispiral) Ĝž¦³Áš«Åš¥¡ 1 Species ‡º° Adamietta housei 2.1.2.2 Genus Brotia Áž¨º°„¤¸¦¼ž¦nµŠ¥µª¦¸ ¤¸ œµ—®œµÂ¨³Ä®n ¥µª ž¦³¤µ– ¤·¨¨·Á¤˜¦ Ÿ·ªÁ¦¸¥®¦º°¤¸­´œÁž}œÁ„¨¸¥ª ­´œ °ŠÁž¨º°„°µ‹ž¦³—´—oª¥ž»i¤„¨¤ 20 -75 Á¨È„Ç ®¦º°®œµ¤ ­nªœ¥°— °ŠÁž¨º°„¤¸¨´„¬–³„¦n°œ (Eroded) ®°¥¤¸žµ„Áž¨º°„„ªoµŠ¦¼žÅ n ¨³

Áž}œÂÁ—È„Žrš¦´¨ (Dextral) ðÁ¡°¦r‡·ª¨´¤ (Operculum) ¤¸¦¼ž¦nµŠ„¨¤Â¨³Áž}œÂ¤´¨˜·­Åž¦´¨ (Multispiral) Áž}œ®°¥š¸É­µ¤µ¦™­º¡´œ›»r‹µ„Å nš¸ÉŤnŗo¦´„µ¦Ÿ­¤‹µ„˜´ªŸ¼o (Parthenogenesis) Ĝ

ž¦³Áš«Åš¥¡ 14 Species ‡º° Brotia pagodula 1. 2. Brotia binodosa binodosa 3. Brotia binodosa subgloriosa 4. Brotia binodosa spiralis 5. Brotia insolita 6. Brotia pseudoasperata 7. Brotia baccata 8. Brotia citrine 9. Brotia manningi 10. Brotia microsculpta 11. Brotia costula 12. Brotia costula varicose 13. Brotia costula peninsularis 14. Brotia (Senckenbergin) wykoffi

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2.1.2.3 Genus Paracrostoma Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦µ¥¥µª‡n°œ oµŠ„¨¤ Áž¨º°„®œµ¤¸­¸œÊ嘵¨Â„n®¦º°­¸Ášµ—ε Ÿ·ªÁž¨º°„Á¦¸¥®¦º°°µ‹¤¸®œµ¤®¦º°˜»n¤˜µ¤Â˜nœ·— °Š®°¥ ˜n¨³œ·— ­nªœ¥°— °ŠÁž¨º°„¤´„¤¸¨´„¬–³„¦n°œ (Eroded) žµ„Áž¨º°„„ªoµŠ¦¼žÅ n¨³Áž}œÂ Á—È„Žrš¦´¨ (Dextral) ðÁ¡°¦r‡·ª¨´¤ (Operculum) Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) Ĝž¦³Áš«Åš¥ ¡ 6 Species ‡º° 1. Paracrostoma pseudosulcospira pseudosulcospira 2. Paracrostoma pseudosulcospira armata 3. Paracrostoma solemiana 4. Paracrostoma paludiformis paludiformis 5. Paracrostoma paludiformis dubiosa 6. Paracrostoma morrisoni ®°¥ªŠ«r š¸É¡Äœž¦³Áš«Åš¥š´ÊŠ ­µ¤µ¦™ÂnŠÁž}œ Thiaridae 8 Genus Species ŗ o 27 Species Ž¹ÉŠ¤¸¦µ¥¨³Á°¸¥— °ŠÂ˜n¨³ Species —´Šœ ¸Ê (Brandt 1974 : 162-189)

1. Tarebia granifera ¨´„¬–³ °Š®°¥œ·— Tarebia granifera ‡º° Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¥µª ¤¸¨´„¬–³®œµÁž}œ­¸Á ¸¥ª®¦º°œÊ嘵¨Ÿ·ªÁž¨º°„Áž}œ­´œÂ¨³ž„‡¨»¤—oª¥ž»i¤

®¦º°˜»n¤„¨¤Á¨È„ (Tubercle) ×¥šªÅž´É ¥°—Áž¨º°„‹³­¹„„¦°œn (Apex eroded) ¤¸Áª·¦r¨ ž¦³¤µ– 3 - 4 Áª·¦r¨ °—¸Áª·¦r¨ ¤¸ œµ—Ä®n ¨ª—¨µ¥œœÁž¨º°„ž¦³„°—oª¥ (Body whorl) Spiral groove ¨³ Axial ribs ×¥Ÿ·ªÁž¨º°„¤¸¨ª—¨µ¥Áž }œ­´œ®¦º° °œ¼œ ž¦³„°—oª¥ 2 spiral grooves ¨¹„ ¨³ 3 spiral rows Áž}œ˜»n¤ ­nªœ“µœÁž¨º°„ (Base) ‹³Áž}œ Spiral ridge Á¡¥Š°¥¸ µŠÁ—n ¸¥ª Áž}œ®°¥š¸É¤¸ žµ„Áž¨º°„Áž}œÂÁ—È„Žrš¦´¨ (Dextral) ¤¸Ã°Á¡°¦r‡·¤¨´¤ (Operculum) ¡°Ž·­Åž¦´¨ (Paucispiral) 2. Thiara scabra ¨´„¬–³ °Š®°¥œ·— Thiara scabra ‡º° Áž¨º°„¤¸ ¦¼ž¦nµŠÁž}œ„¦ª¥¦¸¥µª ¤¸°—¸Áª·¦r¨Ä®n¤¸­¸Á ¸¥ª¤³„°„ Ÿ·ªÁž¨º°„¤®œµ¤¸ µŠ‡¦´ÊŠ‹³¡Â™­¸ œÊ嘵¨ 1 – 3 ™ª (Band) ¨ª—¨µ¥œÁž¨º°„®°¥‹³¤ ¸ Spiral ridges ž¦³¤µ– 5 Á­oœ °µ‹‹³¤µ„„ªnµ ®¦º°œo°¥„ªnµ ¨³Á®ÈœÁ­oœÅ—o°¥nµŠ´—Á‹œ Áž}œ®°¥š¸É¤¸žµ„Áž¨º°„Áž}œÂÁ—È„Žrš¦´¨ (Dextral) ¤¸Ã°Á¡°¦r‡·ª¨´¤ (Operculum) ¦¼žÅ n ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) 3. Sermyla riqueti ¨´„¬–³ °Š®°¥œ·— Sermyla riqueti ‡º° Áž¨º°„ ‡n°œ oµŠÁ¨È„™¹Š œµ—„¨µŠ ¦¼ž¦nµŠÁ¦¸¥ª¥µª®¦º°‡n°œ oµŠ„¨¤ Áª·¦r¨­»—šoµ¥¤¸ œµ—Ä®nž¦³¤µ– ‡¦¹ÉŠ®œ¹ÉŠ °Š‡ªµ¤¥µª °ŠÁž¨º°„ ­nªœœ °Š°—¸Áª·¦r¨ (Body whorl) ¤¸¨ª—¨µ¥š¸É´—Á‹œ Áž}œ ¦n°ŠÁ„¨¸¥ª ¨ª—¨µ¥œ¸ÊÁ¦·É¤‹µ„ Postnuclear whorl

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4. Melanoides tuberculata ¨´„¬–³ °Š®°¥œ·— Melanoides tuberculata ‡º° Áž¨º°„¤¸¦¼ž¦nµŠ¥µª¦ ¸ ¤¸Áª·¦r¨ ž¦³¤µ– 6 – 10 Áª·¦r¨ Ž¹ÉŠ‡n°¥Ç ¤¸ œµ—Ä®n ¹Êœ ¨³ ‹³Á¡·É¤‹ÎµœªœÁª·¦r¨˜µ¤ œµ— °Š®°¥ Áª·¦r¨°µ‹¤¸¨´„¬–³œ¼œ®¦º°Âœ ­nªœ¥°— °ŠÁž¨º°„ (Apex) ¤´„¤¸¨´„¬–³„¦n°œ®¦º°¤¸¨´„¬–³‡¨oµ¥ž¨µ¥˜´— (Truncate) Áž¨º°„¤¸­¸œÊ嘵¨®¦º°­¸Á ¸¥ª¤³„°„ Áž¨º°„Áž}œ­´œ ¨³Ÿ·ªÁž¨º°„ž„‡¨»¤—oª¥ ž»i¤Á¨È„Ç (Tubercle) ¨ª—¨µ¥œÁž¨º°„®°¥‹³¤ ¸ Spiral ridges Áž}œÁ­oœÁ¨È„Ç Áž}œ‹Îµœªœ¤µ„ ¤¸¨ª—¨µ¥Áž}œ­´œ®¦º° °œ¼œ Áž}œ®°¥š¸É¤¸žµ„Áž¨º°„Áž}œÂ Á—È„Žrš¦´¨ (Dextral) ¤¸Ã°Á¡°¦r‡·ª¨´¤ (Operculum) ¦¼žÅ n ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) 5. Melanoides jugicostis ¨´„¬–³ °Š®°¥œ·— Melanoides jugicostis ‡º° Áž¨º°„¤¸¦¼ž¦nµŠ¥µª¦ ¸ œµ—Á¨È„ Ÿ·ªÁž¨º°„Áž}œ­´œœ¼œ (Ribs) ¨³Áž}œ¦n°Š (Grooves) ­¨´„´œ °¥nµŠ´—Á‹œ ¤¸Áª·¦r¨ž¦³¤µ– 5 – 7 Áª·¦r¨ ­nªœ¥°— °ŠÁž¨º°„ (Apex) ¤´„¤¸¨´„¬–³„¦n°œ (Eroded) Áž¨º°„¤¸­¸œÊ嘵¨®¦º°­¸Á ¸¥ª ¡Â™­¸œÊ嘵¨ (Band) °¥¼n¦·Áª–“µœ °ŠÁž¨º°„ Áž}œ®°¥š¸É¤¸ žµ„Áž¨º°„Áž}œÂÁ—È„Žrš¦´¨ ¤¸Ã°Á¡°¦r‡·ª¨´¤ ¦¼žÅ n ¨³Áž}œÂ (Dextral) (Operculum) ¡°Ž·­Åž¦´¨ (Paucispiral)

6. Neoradina prasongi ¨´„¬–³ °Š®°¥œ·— Neoradina prasongi ‡º° Áž¨º°„¤¸¦¼ž¦nµŠÁ¦¸¥ª¥µª ¥°—®¨¤¤¸Á¡¸¥Š ¨¼„®°¥š¸Éž¨µ¥„¦n°œ ¨ª—¨µ¥Áž}œÁ­oœ¨¹„ (Spiral grooves) 2 Áª·¦r¨Â¦„Ÿ·ªÁ¦¸¥ Áª·¦r¨š ¸É 3 – 7 ‹³¤¸¨ª—¨µ¥ÁžœÁ„¨} ¸¥ª ­nªœÁª·¦r¨š ¸É 8 ‹³¤¸¨ª—¨µ¥œo°¥¨Š Á®¨º°Á¡¸¥Š Á­oœÁ®œº°Ž¼Á°¦r Áª·¦r¨­»—šoµ¥¤¸­´œÂ®¨¤‡¤ ¦·Áª–¦³®ªnµŠŽ¼Á°¦r 2- 3 (Suture) (Ridge) (Suture) ¨³ ­´œ (Ridge) ‹³¤¸¨´„¬–³Áª oµ Áž¨º°„ž„‡¨»¤—oª¥´Êœ­¸Á ¸¥ª¤³„°„ žµ„Áž¨º°„¦¼ž¦¸ ðÁ¡°¦r‡·ª¨´¤ (Operculum) Áž}œÂ ¡°Ž·­Åž¦´¨ (Paucispiral)  Eccentric nucleus 7. Adamietta housei ¨´„¬–³ °Š®°¥œ·— Adamietta housei ‡º° Áž¨º°„®°¥¤¸¦¼ž¦nµŠÁž}œš¦Š„¦ª¥ ¤¸ œµ—„¨µŠ Ÿ·ªÁ¦¸¥ ¥„Áªoœ°µ‹¤¸Á­oœ °Š„µ¦Á‹¦·Á˜·Ã˜ ­¸°°„Á®¨º°Šœµ˜µ¨ÊÎ ¤¸¨µ¥ Ÿ·ªÁžœ¤} ´œ ¤´„‹³¡ ž¨µ¥Â®¨¤ µŠ‡¦´ÊŠ°µ‹¡ž¨µ¥˜´— ¤¸Áª·¦r¨ 12 – 14 Áª·¦r¨ ˜n¨³Áª·¦r¨‡n°œ oµŠÂœ ­nªœ°—¸Áª·¦r¨ª´—Å—o œµ— 2/5 °Š‡ªµ¤¥µªÁž¨º°„š´ÊŠ®¤— ° žµ„Áž¨º°„¤¸ œµ—Ä®Ážn }œ¦žÅ ¼ n ¨³Â®¨¤‡¤ Áž}œ®°¥š¸É¤¸žµ„Áž¨º°„Áž}œÂÁ—È„Žš¦r ´¨ (Dextral) ðÁ¡°¦r‡·ª¨´¤ (Operculum) ¤¸¦¼ž¦nµŠ‡n°œ oµŠ„¨¤ ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) 8. Brotia (Brotia) pagodula ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) pagodula ‡º° Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¥µª Áž¨º°„®œµ¤¸­¸œÊ嘵¨ ×¥š´ÉªÅž­nªœ¥°— °ŠÁž¨º°„‹³ ¤¸¨´„¬–³„¦n°œ (Eroded) Ÿ·ªÁž¨º°„®°¥‹³¤¸­´œ (Spiral ridge) ¤¸nµ (Shoulder) ®¦º°¤¸­´œ ° ¥„ ¹Êœ ¨³¤¸˜»n¤œ„¹ÉŠ„¨µŠÁª·¦r¨Â¨³¤¸®œµ¤ 6 – 8 °´œ œ°—¸ÊÁª·¦r¨ ¤¸Áª·¦r¨ž¦³¤µ– 4 Áª·¦r¨ ðÁ¡°¦r‡·ª¨´¤ (Operculum) ¤¸¨´„¬–³„¨¤ ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral)

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9. Brotia (Brotia) binodosa binodosa ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) binodosa binodosa ‡º° Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¦ ¸ ¥µª Áž¨º°„®œµÁž}œ¤´œªµª ¤¸­¸œÊ嘵¨ ®¦º°­¸œÊ嘵¨°°„Á ¸¥ª¤³„°„ ¤¸Áª·¦r¨ž¦³¤µ– 3 – 4 Áª·¦r¨ ‹³¤¸®œµ¤Á¦¸¥ŠÁž}œÂ™ª°¥¼n 2 ™ªÄœ ˜n¨³Áª·¦r¨ Áž¨º°„¤¸®œµ¤®¦º°˜»n¤ ×¥š´ÉªÅž­nªœ¥°— °ŠÁž¨º°„¤´„¤¸¨´„¬–³„¦n°œ (Eroded) ¨³ Ĝ˜n¨³Áª·¦r¨‹³Â¥„°°„‹µ„„´œ Á®ÈœÅ—o°¥nµŠ´—Á‹œ šÎµÄ®oÁ®ÈœŽ¼Á°¦r¨¹„ ×¥®œµ¤ÄœÂœªÂ¦„‹³ °¥¼n„¹ÉŠ„¨µŠ¦³®ªnµŠŽ¼Á°¦r¨³Â™ªš¸É­°Š‹³°¥¼nĄ¨o„´Ž¼Á°¦ r Ÿ·ª¦·Áª–“µœÁž¨º°„—oµœ¨nµŠ‹³¤¸­´œ (Spiral ridge) Áž}œÁ­oœ 4 Á­oœ ­nªœœo°¥‹³¡ 3 ®¦º° 5 Á­oœ ®œµ¤ÄœÂ˜n¨³Â™ª‹³¤¸ž¦³¤µ– 12 °´œ Ĝ˜n¨³Áª¦r¨Â¨³°—¸Áª·¦r¨¤¸®œµ¤ž¦³¤µ– 14 °´œ Áž}œ®°¥š¸É¤¸žµ„Áž¨º°„Áž}œÂÁ—„ŽÈ š¦r ´¨ (Dextral) ðÁ¡°¦r‡·ª¨´¤ (Operculum) ‡n°œ oµŠ„¨¤ Ÿ·ª—oµœÄœ¤´œªµª ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) 10. Brotia (Brotia) binodosa subgloriosa ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) binodosa subgloriosa ‹³˜nµŠ‹µ„œ·—°ºÉœ ˜¦Šš¸ÉŤn¤¸¨ª—¨µ¥Ä—Ç Á¨¥ °µ‹‹³¡˜»n¤

Á¨È„Ç ˜n®µ¥µ„ Apex ¤´„®„„¦´ n°œ ¤¸Áª·¦r¨ 4 – 5 Áª·¦r¨ Á¦¸¥Á­¤°„´œ žµ„Áž¨º°„Ä®n¤¸ œµ— 2/3

°Š‡ªµ¤­¼ŠÁž¨º°„ £µ¥ÄœÁž¨º°„­¸œÊεÁŠ·œ µª 11. Brotia (Brotia) binodosa spiralis ¨´„¬–³ °Š®°¥œ·— Brotia

(Brotia) binodosa spiralis ‡º° Áž¨º°„®°¥¤¸¦¼ž¦nµŠ Áž}œ„¦ª¥Áž¨º°„®œµ ¤¸­¸œÊ嘵¨ ×¥šªÅž­´É nªœ¥°— °ŠÁž¨º°„‹³¤¸¨´„¬–³„¦n°œ ¤¸Áª·¦r¨ž¦³¤µ– Áª·¦r¨ Ÿ·ªÁž¨º°„®°¥‹³¤¸­´œ (Eroded) 4 (Spiral ridge) 4 – 6 Á­oœ ­´œÁ­oœÂ¦„×¥š´ÉªÅž¤´„‹³®µ¥Åž Ťn¤¸®œµ¤ µŠ‡¦´ÊŠ˜¦Š­´œ°µ‹‹³¤¸¨´„¬–³Áž}œ Á¤È—œ¼œÁ¨È„Ç ¹Êœ¤µš¸ÉŸ·ªÁž¨º°„®°¥„Èŗo ðÁ¡°¦r‡·ª¨´¤ (Operculum) ¤¸¨´„¬–³‡n°œ oµŠ„¨¤ ¨³ Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) 12. Brotia (Brotia) insolita ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) insolita ‡º° Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¥µª¦ ¸ ¤¸ œµ—Á¨È„ Áž¨º°„Ťn®œµ ¤¸­¸Ášµ—ε ®¦º°­¸Á ¸¥ª¤³„°„ ×¥š´ÉªÅž­nªœ¥°— °ŠÁž¨°„‹³¤º ¸¨´„¬–³„¦n°œ (Erodes) ¤¸Áª·¦r¨ž¦³¤µ– 3 – 5 Áª·¦r¨ ¨³¤¸ ‹ÎµœªœÁ¡ºÉ¤¤µ„ ¹Êœ˜µ¤ œµ— °ŠÁž¨º°„®°¥ ¤¸°—Áª¸ ·¦r¨ œµ—Ä®nÁžœ‡¦} ¹ÉŠ®œ¹ÉŠ °Š‡ªµ¤¥µªÁž¨º°„ ×¥š´ÉªÅž‹³Å¤n¡Â™­¸œÊ嘵¨œŸ·ªÁž¨º°„ µŠ‡¦´ÊŠ °µ‹‹³¡ Spiral ridge š¸É­nªœ“µœ °Š°—¸ Áª·¦r¨ Ž¼Á°¦r¨¹„ °žµ„Áž¨º°„¤¸ œµ—Ä®nÁž}œ¦¼žÅ n £µ¥Äœ¤¸­¸œÊ嘵¨®¦º° µª ðÁ¡°¦r‡·ª¨´¤¤¸ œµ—Á¨È„ ¦¼ž¦nµŠ„¨¤ ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) 13. Brotia (Brotia) pseudoasperata ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) pseudoasperata œµ—¨³¦¼ž¦nµŠ‡¨oµ¥„´ B. insolita ˜n¨ª—¨µ¥¤ ¸ Spiral ridge ¤µ„¤µ¥ ¤¸

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Spiny tubercles ˜n¦·Áª– Spiral ridge š¸É 2 ‹³Å¤n¤¸ Tubercle °žµ„Áž¨º°„Ážœ¦} ¼ž¦ ¸ ðÁ¡°¦r‡·ª¨´¤ (Operculum) Áž}œªŠ„¨¤ 14. Brotia (Brotia) baccata ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) baccata ‡º° Ťn¤¸®œµ¤ (Spine) ¨³¤ ¸ Spiral ridge Áž}œ˜»n¤ (Tubercles) ®¦º°  (Nodules) Áž¨º°„¤¸¦¼ž¦nµŠÁ¦¸¥ª¥µª ®¦°‡º n°œ oµŠ„¨¤ Apex ¤´„­„„¦¹ n°œ ¤¸Ž¼Á°¦ r (Suture) ¨¹„ Áž¨º°„ž„‡¨»¤ —oª¥œ­´Ê ¸Á ¸¥ª¤³„°„ ¤¸ 3 Spiral ridge š¸É Upper whorl ¨³ 6 -7 œ°—¸Áª·¦r¨ (Body whorl) —oµœœ °Š Spiral ridges ‹³¤ ¸ Tubercle ®¦º° Nodules °žµ„Áž¨º°„¤¸ œµ—ž¦³¤µ– 2/3 °Š ‡ªµ¤­¼ŠÁž¨º°„ 15.Brotia (Brotia) citrine ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) citrine ‡º° œµ—Ä®n„ªnµœ·— B. Insolita Áž¨º°„‡n°œ oµŠÂ Ȋ ŤnÞ¦nŠÂ­Š ­¸Á®¨º°ŠÁ ¸¥ª®¦º° Á ¸¥ª¤³„°„®¦º°°„œÊ嘵¨ ˜n×¥šªÅž‹³´É ž„‡¨»¤—ª¥o ´Êœ­¸—ε °ŠÂ¦n›µ˜ » Apex ¤´„­¹„„¦n°œ ¤¸ Áª·¦r¨ Áª·¦r¨ Ÿ·ªÁ¦¥¸ ¥„Áªœ¦o Áª–· Áª¦¨­r »—šoµ¥¤¸ µŠÇ °žµ„Áž¨º°„ 9 – 11 Growth lines Spiral line Áž}œ¦¼ž¦ ¸

16. Brotia (Brotia) manningi ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) manningi ‡º° Áž¨º°„®°¥¤¸¦¼ž¦nµŠÁž}œ„¦ª¥ ¤¸ œµ—Ä® n ¦¼ž¦nµŠ­nªœ“µœ °ŠÁž¨º°„‡n°¥ oµŠ„ªoµŠ

Áª·¦r¨¤¸¨´„¬–³Âœ¦µ ¨³¤¸ œµ—Ä®n„ªnµ Brotia (Brotia) insolita ×¥š´ÉªÅž‹³¤¸Ÿ·ªÁž¨º°„Á¦¸¥ ˜n¤¸¨µ¥Á­oœÄœÂœª˜´ÊŠ Ťn‡n°¥Á¦¸¥ Áž¨º°„®œµ¤¸­¸Ášµ—宦º°œÊ嘵¨Â„n °žµ„Áž¨º°„ (Growth line) ¤¸ œµ—Ä®nÁž}œ¦¼žÅ n £µ¥Äœ¤¸­¸ µª ðÁ¡°¦ r‡·ª¨´¤ (Operculum) ¤¸‡n°œ oµŠ„¨¤ ¨³Áž}œÂ ¡°Ž·­Åž¦´¨ (Paucispiral) 17. Brotia (Brotia) microsculpta ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) microsculpta ‹³¤‡ªµ¤Â˜„˜¸ nµŠ‹µ„‹¸œ´­Brotia œ·—°ºÉœÁ®œÅ—È o´—Á‹œ ‡º°Áž¨º°„¤¸ œµ— Á¨È„¨³¤ ¸ Spiral microsculpture Á®ÈœÅ—°¥o nµŠ´—Á‹œ Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¤´œªµª ¤¸­¸œÊ嘵¨ ®¦º°­¸Á ¸¥ª¤³„°„ ­nªœ¥°— °ŠÁž¨º°„¤´„¤¸¨´„¬–³ „¦°œn (Eroded) ¦·Áª–­ªœn °—¸Áª·¦r¨‹³¤¸­´œ ˜µ¤¥µª¡µ—°¥¼n—oµœ“µœ °ŠÁž¨º°„ ¨³µŠ‡¦´ÊŠ°µ‹¡Â™­¸œÊ嘵¨ 1 – 2 ™ °žµ„Áž¨º°„¤¸ œµ—Ä® n ×¥šªÅž¤´É ¸ œµ— 2/3 °Š‡ªµ¤­¼Š °Š°—¸Áª·¦r¨ £µ¥Äœ‹³¤¸­¸ µª®¦º°­¸œÊ嘵¨ Áž}œ ®°¥š¸É¤¸žµ„Áž¨º°„Á—È„Žrš¦´¨ (Dextral) ­nªœÃ°Á¡°¦r‡·ª¨´¤ (Operculum) ¤¸¦¼ž¦nµŠ‡n°œ oµŠ„¨¤ ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) 18. Brotia (Brotia) costula costula ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) costula costula ‡º° Áž¨º°„¤¸ œµ—Ä®n­Îµ®¦´Äœ Family œ¸Ê ¨³ Genus œ¸Ê ¨³Ä®nš¸É­»— ­Îµ®¦´Äœž¦³Áš«Åš¥ Áž¨°„Á¦º ¸¥ª¥µª  Ȋ¨³®œµ ž„‡¨»¤—oª¥œ­´Ê ¸œÊ嘵¨—ε ®¦º°œÊ嘵¨Á ¸¥ª

38

­nªœ¥°—¤¸¨´„¬–³žjµœ ¨ª—¨µ¥Áž}œ Spiral groove Ážœ¨µ¥µŠÇ} —oµœœ ¨³°µ‹‹³¤ ¸ Nodules Á¤ºÉ°¤¸„µ¦Á‹¦·Á˜È¤š ¸É ¨³°µ‹‹³¡ Spine ­´ÊœÇ ¤¸ Axial rib ´—Á‹œ žµ„Áž¨º°„£µ¥Äœ­¸œÊ嘵¨®¦º° µªÃ°Á¡°¦r‡·ª¨´¤ (Operculum) ¤¸¦¼ž¦nµŠ„¨¤ 19. Brotia (Brotia) costula varicose ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) costula varicosa ‹³˜nµŠ‹µ„­µ¥¡´œ›»r°ºÉœ˜¦Šš¸É¤¸Áž¨º°„ Ȋ¨³¤ ¸ Axial rib ¨ª—¨µ¥Áž}œ Á„¨¸¥ª˜¦Š„¨µŠÁª·¦r¨ ¨³­nªœœ¦¼ž¦nµŠÁ¦¸¥ª š¸É Upper end rib °µ‹‹³Áž¨¸É¥œÁž}œ Spine š¸ÉÁª·¦r¨‹³¤ ¸ Nodule 1 -2 ™ª 20. Brotia (Brotia) costula peninsularis ¨´„¬–³ °Š®°¥œ·— Brotia (Brotia) costula peninsularis ‡º° Áž¨º°„¤¸ œµ—Á¨È„¦ž¦¼ nµŠÁ¦¸¥ª¥µª ‡¨oµ¥„´ B.pseudoasperata ®¦º°Áž}œ¦¼ž„¦ª¥„¨¤‡¨oµ¥ Tarebia granifera ­¸œÊ嘵¨ ®¦º°Á ¸¥ª¤³„°„ ¤¸¨ª—¨µ¥µŠÇ ¦·Áª– °—¸Áª·¦r¨Ášnµœ´Êœ ˜n­nªœÄ®n¤´„¤¸¨ª—¨µ¥´—Á‹œ Brotia (Senckenbergin) wykoffi ¨´„¬–³ °Š®°¥œ·— Brotia 21. (Senckenbergin) wykoffi ‡º° Áž¨º°„®°¥¤¸¦¼ž¦nµŠÁžœ„¦ª¥¥µª} Áž¨º°„ Ȋ¨³¤¸¨´„¬–³„ŠÃž¦¹É nŠÂ­Š

¤¸­¸œÊ嘵¨Â—Š ¨³¤¸Â™­¸œÊ嘵¨ 3 ™ (Band) ­µ¤µ¦™¤°ŠÁ®ÈœÂ™Å—oץ™‹³°¥Á®œ¼n º°Áª·¦r¨ Ž¹ÉŠÂ™Â¦„‹³°¥¼nĘoŽ¼Á°¦ r (Suture) ™š ¸É 2 ‹³°¥¼n˜É娊¤µ™´—‹µ„™Â¦„ ¨³Â™š ¸É 3 ‹³°¥¼n

šµŠ—oµœ­nªœ“µœ °Š°—¸Áª·¦r¨ ¤¸¨µ¥Á­oœÄœÂœª˜´ÊŠ (Growth line) ¦·Áª–Ÿª‡· n°œ oµŠ ¦» ¦³ ¨³¤¸ ­´œ ˜¦Š“µœ °ŠÁž¨º°„¦·Áª–°—¸Áª·¦r¨Á®ÈœÅ¤n‡n°¥´—Á‹œ¤µ„œ´„ ­nªœ¥°— °Š (Spiral ridges) Áž¨º°„¤´„¤¸¨´„¬–³„¦n°œ (Eroded) ¤¸Áª ·¦r¨ ž¦³¤µ– 6 – 7 Áª·¦r¨ °žµ„Áž¨º°„Ážœ¦} ¼žÅ n £µ¥Äœ ¤¸­¸¤nªŠ®¦º°­ µª¸ ­µ¤µ¦™­´ŠÁ„˜Á®ÈœÂ™Å—°¥o nµŠ—Á‹œ´ Ážœ®°¥š} ¸É¤¸žµ„Áž¨º°„Áž}œÂÁ—È„Žš¦r ´¨ (Dextral) ðÁ¡°¦r‡·ª¨´¤ (Operculum) ¦¼žÅ n ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral) 22. Paracrostoma pseudosulcospira pseudosulcospira ¨´„¬–³ °Š ®°¥œ·— Paracrostoma pseudosulcospira pseudosulcospira ‡º°Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¦¥µª¸ ¤¸­¸ œÊ嘵¨®¦º°­¸Á ¸¥ª¤³„°„ °—¸Áª·¦r¨¤¸ œµ—Ä® n ¤¸‡ªµ¤­¼Š ž¦³¤µ– 3 / 4 °ŠÁž¨º°„ ­nªœ¥°— °ŠÁž¨º°„¤´„¤¸¨´„¬–³„¦n°œ (Eroded) ¤¸Ž¼Á°¦ r (Suture) ˜ºÊœ ¨ª—¨µ¥œÁž¨º°„®°¥¤¸¨´„¬–³Áž}œ Á­oœÁ¨È„Ç ¨³Á°¸¥— (Spiral microsculpture) Áž¨º°„®œµ¤´œªµª ®°¥Äœ„¨»n¤œ¸Ê‹³Å¤n¤¸Â™œÁž¨º°„ ­nªœÄ®nÁª·¦r¨‹³¤¸¨´„¬–³Âœ¦µ (Flat) °žµ„Áž¨º°„¤¸ œµ—Ä®n¦¼žÅ n Ÿ·ª£µ¥ÄœÁž}œ­¸ œÊεÁŠ·œ®¦º°­¸ µª Áž}œ®°¥š¸É¤¸žµ„Áž¨º°„Áž}œÂÁ—„ŽÈ š¦r ´¨ (Dextral) ðÁ¡°¦r‡·ª¨´¤ (Operculum) ¦¼žÅ n ¨³Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral)

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23. Paracrostoma pseudosulcospira armata ¨´„¬–³ °Š®°¥œ·— Paracrostoma pseudosulcospira armata ˜nµŠ„´­µ¥¡œ›´ »r°ºÉœ˜¦Šš¸É¤¸ 3 Spiral cord œ Upper whorl ¨³ 3 -5 cord œ°—¸ÊÁª·¦r¨ Spiral cord š¸É 1 ¨³ 2 ‹³¤ ¸ Tubercle Ž¹ÉŠ°µ‹Áž¨¸É¥œÁž}œ Spine 24. Paracrostoma solemiana ¨´„¬–³ °Š®°¥œ·— Paracrostoma solemiana ˜nµŠ„´ P. pseudosulcospira ˜¦Šš¸É¦¼ž¦nµŠÁ¡¦¸¥ª„ªnµ µŠ„ªnµ Ÿ·ªÁ¦¸¥ Áž¨º°„­¸œÊ嘵¨ ‡n°œ oµŠ­ªnµŠÅ¤n¤¸ Spiral grooves žµ„Áž¨º°„ oµŠÄœ­¸ µªœÊεÁŠ·œ ¤¸Ã°Á¡°¦r‡·ª¨´¤ (Operculum) œµ—Á¨È„ 25. Paracrostoma paludiformis paludiformis ¨´„¬–³ °Š®°¥œ·— paludiformis paludiformis ‡º° Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¦ ¸ ‡n°œ oµŠÁ˜¸Ê¥ ¤¸­¸œÊ嘵¨Â—Š®¦º°­¸Ášµ—ε °—¸Áª·¦r¨¤¸ œµ—Ä®Â¨³„¨¤n (Round) ­nªœ¥°— °ŠÁž¨º°„¤´„¤¸¨´„¬–³„¦n°œ (Eroded) ×¥š´ÉªÅž ¤¸Áª·¦r¨ 2 Áª·¦r¨ Áž¨º°„¤´œªµª Ÿ·ªÁž¨º°„ŤnÁ¦¥¤µ„œ¸ ´„ Áž¨º°„Á¤ºÉ°¥´ŠÅ¤Á‹¦n ·Á˜Ã˜Á˜· ¤šÈ ¸É (Immature) ‹³¤¸ Áž}œ¦n°Š¨¹„—Á‹œ´ ˜nÁ¤ºÉ°Ážœ˜} ´ªÁ˜È¤ª´¥ ‹³¤¸¦n°Šš¸É˜ºÊœ¤µ„ ¹Êœ °žµ„Áž¨º°„ Spiral cord (Adult) ¤¸ œµ—„ªoµŠ¦¼žÅ n ¤¸Ã°Á¡°¦r‡·ª¨´¤ (Operculum) Áž}œÂ¡°Ž·­Åž¦´¨ (Paucispiral)

26. Paracrostoma paludiformis dubiosa ¨´„¬–³ °Š®°¥œ·— Paracrostoma paludiformis dubiosa ‡º° Áž¨º°„¤¸¦¼ž¦nµŠÁž}œ„¦ª¥¥µª¦¸ ¤¸­¸œÊ嘵¨Â„n®¦º°Ášµ—ε

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9. Paracrostoma paludiformis paludiformis 10. Paracrostoma pseudosulcospira pseudosulcospira 11. Brotia (Brotia) costula costula 12. Brotia (Senckenbergia) wykoffi 13. Brotia (Brotia) microsculpta 14. Brotia (Brotia) maningi 15. Brotia (Brotia) citrina 16. Brotia (Brotia) binodosa binodosa 17. Brotia (Brotia) baccata 1.2 „ε®œ—®¨nŠ‡ªµ¤¦¼o ®¨nŠ‡ªµ¤¦¼oš¸ÉčoĜ„µ¦«¹„¬µÂ¨³¦ª¦ª¤ o°¤¼¨š¸É‹ÎµÁž}œ˜n°„µ¦‹ÎµÂœ„ž¦³Á£š °Š®°¥ ­Îµ®¦´„µ¦¡´•œµ¦³Ÿ¼oÁ¸É¥ªµÄœ„µ¦‹ÎµÂœ„œ·— °Š®°¥œÊε‹º—ªŠ«r ¤¸—´Šœ¸Ê Thiaridae 1.2.1 ®¨nŠ‡ªµ¤¦¼ož¦³Á£š®œ´Š­º° ˜Îµ¦µšµŠ­´–“µœª·š¥µ °Š®°¥ ×¥«¹„¬µ™¹Š

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4. œµ— °Š®°¥Äœ®°¥œ·— Thiaridae 5. ¨´„¬–³ °Š¦n°ŠÅŽ¢°œ (Siphon) 6. œ·—ðÁ¡°¦r‡·ª¨´¤ (Operculum) 7. ¦¼ž¦nµŠÃ°Á¡°¦r‡·ª¨´¤ (Operculum) 8. ¨´„¬–³­´œš“µœÁž¨¸É º°„ 9. ‹Îµœªœ¨µ¥Á­œÄœÂœª ªµŠœ°—o ¸Áª·¦r¨ (Body Whorl) 10. ‹ÎµœªœÂ™ª °Š˜»n¤ (Tubercle) 11. ‡ªµ¤®œµ 12. ¨´„¬–³‡ªµ¤¨³Á°¸¥— °Š¨µ¥Á­oœœŸ·ªÁž¨º°„ 13. œµ—‡ªµ¤­¼Š °Š °žµ„Áž¨º°„ (Aperture) 14. œµ—°—¸Áª·¦r¨ (Body Whorl) ¨´„¬–³Ž¼Á°¦r 15. (Suture) 16. ¦¼ž¦nµŠ °žµ„Áž¨º°„ (Apeture)

17. ‹ÎµœªœÂ™ª °Š®œµ¤ (Spine) 18. ¨´„¬–³¨µ¥Á­œ¨o ¹„ (Spiral grooves) ¦·Áª–¨µ¥Á­oœÂ¨³‡ªµ¤—Á‹œ °ŠÁ­´ oœ 19. ¨µ¥¦·Áª–“µœÁž¨º°„ 20. 21. ¦¼ž¦nµŠ°—¸Áª·¦r¨ (Body Whorl) 22. ¨´„¬–³ °Š­¸Áž¨º°„ 23. ¦¼ž¦nµŠ“µœ °žµ„Áž¨º°„ (Apeture) 24. ­¸¨µ¥Á­oœÄœÂœªœ°œ °ŠÁž¨º°„ 25. ¦¼ž¦nµŠ °ŠÁž¨º°„ 26. œµ— °ŠÁž¨º°„ 27. ‹ÎµœªœÁª·¦r¨ (Whorl) 28. ­¸Áž¨º°„ 29. ¨´„¬–³ °Š­´œÄœÂœªÂ„œ˜´ÊŠ °ŠÁž¨º°„ 30. ¨´„¬–³Ÿ·ªÁž¨º°„

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=== Run information === Scheme:weka.classifiers.trees.J48 -C 0.25 -M 2 Relation: shell Instances:151 Attributes:31 num_Operculum

apex ShapOvalElongCircle ShellMediumToLarght Have_siphon

operculum

oper_shap ripspiral_based VerticalLine3_6-7Body tubercleRows2_3 thick lineChar_surface aper2in3ofBody body_bigCircle suture aperWideOval num_rowsSpine spiralGrooves2Line_tubercle3Rows

£µ¡š ¸É 11 Ÿ¨¨´¡›rĜ„µ¦­¦oµŠ˜oœÅ¤o˜´—­œÄ‹· WEKA 61

spiralLineBody_weakAxialRib ribOnlyBased_lineRipAxial body_size color_char aper_based brownLine horizontal shell_shap size num_whorl color rib_diagonal

surface

species Test mode:10-fold cross-validation

=== Classifier model (full training set) ===

J48 pruned tree ------

apex = yes | num_Operculum <= 1 | | operculum = paucispiral | | | color_char = axial brown: adamietta housie (2.0) | | | color_char = 3 spiral band on body: none (2.0) | | | color_char = one color | | | | body_size = height 2/5 of shell | | | | | spiralGrooves2Line_tubercle3Rows = no | | | | | | spiralLineBody_weakAxialRib = no | | | | | | | ribOnlyBased_lineRipAxial = no: neoradina prasongi (2.0)

£µ¡š ¸É 12 Ÿ¨¨´¡›rĜ„µ¦­¦oµŠ˜oœÅ¤o˜´—­·œÄ‹ WEKA 62

| | | | | | | ribOnlyBased_lineRipAxial = yes: melanoides jugicostis (2.0) | | | | | | spiralLineBody_weakAxialRib = yes: melanoides tuberculata (2.0) | | | | | spiralGrooves2Line_tubercle3Rows = yes: tarebia granifera (2.0) | | | | body_size = more 1/2 of height: thiara scabra (3.0/1.0) | | operculum = multispiral | | | lineChar_surface = none | | | | VerticalLine3_6-7Body = no | | | | | aperWideOval = no | | | | | | body_size = height 2/5 of shell | | | | | | | num_rowsSpine <= 1 | | | | | | | | size = height 0.8 cm. - 3.5 c.m. wide 0.2 cm. - 1.5 cm.: B. wykoffi (2.0) | | | | | | | | size = height more 3.5 c.m. wide 0.5 cm. - 2.5 cm.: B. citrina (2.0)

| | | | | | | num_rowsSpine > 1: B. binodosa (2.0) | | | | | | body_size = more 1/2 of height | | | | | | | oper_shap = oval: para. Dubiosa (2.0) | | | | | | | oper_shap = circle: para. Pseudosulcospira (2.0)

| | | | | aperWideOval = yes

| | | | | | thick = no: para. Paludiformis (2.0) | | | | | | thick = yes: B. maningi (2.0) | | | | VerticalLine3_6-7Body = yes: B. baccata (4.0) | | | lineChar_surface = Strong: B. costula (2.0) | | | lineChar_surface = Small: B. microsculpta (2.0) | num_Operculum > 1: none (39.0/1.0) apex = no: none (75.0) Number of Leaves : 19 Size of the tree : 35 Time taken to build model: 0.07seconds

=== Stratified cross-validation ======Summary ===

£µ¡š ¸É 13 Ÿ¨¨´¡›rĜ„µ¦­¦oµŠ˜oœÅ¤o˜´—­œÄ‹· WEKA 63

Correctly Classified Instances 132 87.4172 % Incorrectly Classified Instances 19 12.5828 % Kappa statistic 0.6942 Mean absolute error 0.013 Root mean squared error 0.091 Relative absolute error 24.3402 % Root relative squared error 59.113 % Total Number of Instances 151 === Confusion Matrix === a b c d e f g h i j k l m n o p q r <-- classified as 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 | a = adamietta housie

0 115 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 | b = none

0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 | c = neoradina prasongi 0 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 | d = thiara scabra 0 1 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 | e = sermyla requeti

0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 | f = tarebia granifera

0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 | g = melanoides jugicostis 0 0 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 | h = melanoides tuberculata

0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 | i = para. Dubiosa 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 | j = para. Paludiformis 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 0 0 0 | k = para. Pseudosulcospira 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 0 | l = B. costula 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 | m = B. wykoffi 0 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 | n = B. microsculpta 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 | o = B. maningi 0 0 0 0 0 0 0 0 0 0 0 0 2 0 0 0 0 0 | p = B. citrina 0 0 0 0 0 0 0 0 0 0 0 0 1 0 1 0 0 0 | q = B. binodosa 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 4 | r = B. baccata

£µ¡š ¸É 14 Ÿ¨¨´¡›rĜ„µ¦­¦oµŠ˜oœÅ¤o˜´—­·œÄ‹ WEKA 64

Ÿ¨¨´¡›rš¸Éŗo‹µ„ WEKA ž¦³„°—oª¥­nªœ˜nµŠÇ —´Šœ ¸Ê 1. ­nªœš¸É­—Š o°¤¼¨š¸ÉčoĜ„µ¦­¦oµŠ˜oœÅ¤o˜´—­·œÄ‹ (Run information) °„™¹Š ´Êœ˜°œª·›¸š¸Éč o ºÉ°˜µ¦µŠ o°¤¼¨ (Relation) ‹Îµœªœ˜´ª°¥nµŠš´ÊŠ®¤—š¸Éč o (Instances) ‹ÎµœªœÂ¨³ºÉ° ¨´„¬–³ž¦³‹Îµ (Attibute) ¨³ª·›¸„µ¦š—­° (Test mode) 2. ­nªœÂ­—Š˜oœÅ¤oš¸Éŗo‹µ„„µ¦‹ÎµÂœ„ (Classifier model) Ž¹ÉŠ®µ„­¦oµŠ˜oœÅ¤oĜ ަ„¦¤ WEKA ­µ¤µ¦™Â­—ŠŸ¨¨´¡›rÁž}œ„¦µ¢d„¦¼ž˜oœÅ¤oŗo (£µ¡š¸É 15) ¨³‹ÎµœªœÄ °Š ˜oœÅ¤ o œµ— °Š˜oœÅ¤ o ¦ª¤š´ÊŠÁª¨µž¦³¤ª¨Ÿ¨ 3. ­nªœÂ­—Š‡nµ‡ªµ¤™¼„˜o°Š °Š„µ¦š—­°‹µ„ o°¤¼¨š—­° ¦ª¤š´ÊŠ‡nµ­™·˜· ˜nµŠÇ (Stratified cross-validation Confusion Matrix) Á¡ºÉ°Â­—Š‡ªµ¤Â¤nœ¥ÎµÄœ„µ¦Äo˜oœÅ¤oš¸É­¦oµŠ ¹ÊœÄœ„µ¦‹ÎµÂœ„ o°¤¼¨ Ž¹ÉŠž¦³„°—oª¥ ‡nµ˜´ª°¥nµŠš¸É™¼„˜o°Š (Correctly Classified Instances) Ĝ š¸Éœ¸É˜oœÅ¤oš¸É­¦oµŠ ¹Êœ­µ¤µ¦™‹ÎµÂœ„Å—o 132 ˜´ª°¥nµŠ‹µ„ 151 ˜´ª°¥nµŠ ‡·—Áž}œ 87.4172 % ¨³ ‹ÎµÂœ„Ÿ·— ˜´ª°¥nµŠ‹µ„ ˜´ª°¥nµŠ ‡·—Áž}œ ¦ª¤š´ÊŠ„µ¦ž¦³Á¤·œŸ¨¨´¡›r„µ¦šÎµœµ¥ 19 151 12.5828 % Áš¸¥„´Ÿ¨¨´¡›r‹¦·ŠŽ¹ÉŠ°¥¼nĜ¦¼ž °Š˜µ¦µŠÂÅ ªo„´œ (Confusion Matrix)

£µ¡š ¸É 15 ˜oœÅ¤o˜´—­·œÄ‹šÅ—¸É o‹µ„ަ„¦¤ WEKA 65

66

´Êœ˜°œ„µ¦Âšœ‡ªµ¤¦¼o ‹³œÎµŸ¨Ÿ¨¨´¡›rš¸Éŗo‹µ„„µ¦‹ÎµÂœ„ž¦³Á£š—oª¥˜oœÅ¤o ˜´—­·œÄ‹¤µÂž¨ŠÁž}œ„‘Á¡ºÉ°‹³Âšœ‡ªµ¤¦¼oĜ¦¼ž °Š„‘ Ž¹ÉŠ‹µ„˜oœÅ¤o˜´—­·œÄ‹š¸Éŗo ­µ¤µ¦™Âšœ ‡ªµ¤¦¼oÁž}œ„‘Å—oš´ÊŠ®¤— 19 „‘ —´Šœ ¸Ê 1. RULE 1 : IF apex = no THEN species = none 2. RULE 2 : IF apex = yes and num_Operculum > 1 THEN species = none 3. RULE 3 : IF apex = yes and num_Operculum <= 1

operculum = multispiral lineChar_surface = small

THEN species = Brotia (Brotia) microsculpta 4. RULE 4 : IF apex = yes and

num_Operculum <= 1

operculum = multispiral lineChar_surface = strong THEN species = Brotia (Brotia) costula costula 5. RULE 5 : IF apex = yes and num_Operculum <= 1 operculum = multispiral lineChar_surface = none verticalLine3_6-7Body = yes THEN species = Brotia (Brotia) baccata 6. RULE 6 : IF apex = yes and num_Operculum <= 1 operculum = multispiral lineChar_surface = none verticalLine3_6-7Body = no 67

aperWideOval = yes thick = yes THEN species = Brotia (Brotia) maningi 7. RULE 7 : IF apex = yes and num_Operculum <= 1 operculum = multispiral lineChar_surface = none verticalLine3_6-7Body = no aperWideOval = yes thick = no THEN species = Paracrostoma paludiformis paludiformis

8. RULE 8 : IF apex = yes and num_Operculum <= 1

operculum = multispiral lineChar_surface = none

verticalLine3_6-7Body = no

aperWideOval = no body_size = more ½ of height oper_shap = circle THEN species = Paracrostoma pseudosulcospira pseudosulcospira 9. RULE 9 : IF apex = yes and num_Operculum <= 1 operculum = multispiral lineChar_surface = none verticalLine3_6-7Body = no aperWideOval = no body_size = more ½ of height oper_shap = oval THEN species = Paracrostoma paludiformis dubiosa

68

10. RULE 10 : IF apex = yes and num_Operculum <= 1 operculum = multispiral lineChar_surface = none verticalLine3_6-7Body = no aperWideOval = no body_size = height 2/5 of shell num_rowsSpine >1 THEN species = Brotia (Brotia) binodosa binodosa 11. RULE 11 : IF apex = yes and num_Operculum <= 1

operculum = multispiral lineChar_surface = none

verticalLine3_6-7Body = no aperWideOval = no

body_size = height 2/5 of shell

num_rowsSpine <=1 size = height more 3.5 cm. wide 0.5 cm. – 2.5 cm. THEN species = Brotia (Brotia) citrina 12. RULE 12 : IF apex = yes and num_Operculum <= 1 operculum = multispiral lineChar_surface = none verticalLine3_6-7Body = no aperWideOval = no body_size = height 2/5 of shell num_rowsSpine <=1 size = height 0.8 cm. – 3.5 cm. wide 0.2 cm. – 1.5 cm. THEN species = Brotia (Senckenbergia) wykoffi

69

13. RULE 13 : IF apex = yes and num_Operculum <= 1 operculum = paucispiral color_char = one color body_size = more ½ of height THEN species = Thiara scabra 14. RULE 14 : IF apex = yes and num_Operculum <= 1 operculum = paucispiral color_char = one color body_size = more 2/5 of shell

spiralGrooves2Line_tubercle 3 Rows = yes THEN species = Tarebia granifera

15. RULE 15 : IF apex = yes and num_Operculum <= 1

operculum = paucispiral

color_char = one color body_size = more 2/5 of shell spiralGrooves2Line_tubercle 3 Rows = no spiralLineBody_weakAxailRib = yes THEN species = Melanoides tuberculata 16. RULE 16 : IF apex = yes and num_Operculum <= 1 operculum = paucispiral color_char = one color body_size = more 2/5 of shell spiralGrooves2Line_tubercle 3 Rows = no spiralLineBody_weakAxailRib = no ribOnlyBased_lineRibAxial = yes THEN species = Melanoides jugicostis 70

17. RULE 17 : IF apex = yes and num_Operculum <= 1 operculum = paucispiral color_char = one color body_size = more 2/5 of shell spiralGrooves2Line_tubercle 3 Rows = no spiralLineBody_weakAxailRib = no ribOnlyBased_lineRibAxial = no THEN species = Neoradina prasongi 18. RULE 18 : IF apex = yes and num_Operculum <= 1

operculum = paucispiral color_char = 3 spiral band on body

THEN species = none 19. RULE 19 : IF apex = yes and

num_Operculum <= 1

operculum = paucispiral color_char = axial brown THEN species = Adamietta housei

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( N1 [label="num_Operculum" ] ) = ( N1->N2 [label="<= 1"] ) AND ( N2 [label="operculum" ] ) = ( N2->N15 [label="= multispiral"] ) AND

( N15 [label="lineChar_surface" ] ) = N15->N32 [label="= Small"] THEN ( N32 [label="B. microsculpta"] )

Rule 3. IF (N0 [label="apex" ] ) = ( N0->N1 [label="= yes"] ) AND

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¨³ lineChar_surface = small ¦³‹³­µ¤µ¦™­¦»ž„‘Å— o Ž¹ÉŠ„‘šÁž¸É }œ‹¦·Š‡º°„‘ o° 2 œ·— °Š ®°¥‡º° B. microsculpta ÁœºÉ°Š‹µ„Å—o‡nµ‡ªµ¤‹¦·Š˜¦Š„­´ nªœÁŠºÉ°œÅ °Š„‘š»„ž¦³„µ¦

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grooves 2 Á­oœÄœÂœªœ°œ ¨³¤¸˜»n¤ 3 ™ªš¸É °—¸Áª·¦r¨ (Body whorl) ¤¸Á­oœÄœÂœªœ°œš´Éªš´ÊŠÁž¨º°„ ¨³¤¸­´œÄœÂœª˜´ÊŠ µŠÇ ¤¸Á­oœœ¼œÄœÂœªœ°œÁŒ¡µ³“µœÁž¨º°„ ­nªœÄœÂœª˜´ÊŠ ¤¸­´œœ¼œÁ­oœÁ¨È„´—Á‹œ Ĝ˜n¨³Áª·¦r¨ (Whorl) ¤¸¨µ¥Á­oœ˜µ¤Âœª ªµŠ 3 Á­oœ 3 ¨³°—¸Áª·¦r¨ (Body whorl) ¤¸ 6-7 Á­oœ

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1. Áž¨º°„¤¸‡ªµ¤¥µª 0.8 cm. ™¹Š 3.5 cm. 3 3 3 ¨³¤¸‡ªµ¤„ªoµŠ ™¹Š 0.2 cm. 1.5 cm. 2. Áž¨º°„¤¸‡ªµ¤¥µª¤µ„„ªnµ 3.5 cm. ¹Êœ 3 3 3 3 3 Ş ¨³¤¸‡ªµ¤„ªoµŠ 0.5 cm. ™¹Š 2.5 cm.

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thick ‡ªµ¤®œµ text -

lineChar_surface ¨´„¬–³‡ªµ¤¨³Á°¸¥— °Š¨µ¥Á­oœ text - œŸ ·ªÁž¨º°„

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108

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species œ·— °Š®°¥ text -

˜µ¦µŠš ¸É 7 ǦŠ­¦oµŠ˜µ¦µŠ CURRENT-TREE ºÉ°‡°¨´¤œ r ‡Îµ°›·µ¥ œ·— PK/FK

id ¦®´­ Vachar(11) PK

cls ¦µ¥¨³Á°¸¥— text -

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110

˜µ¦µŠš ¸É 9 ˜´ª°¥nµŠ®°¥ ¨Îµ—´š ¸É œ·— °Š®°¥ ¦¼ž£µ¡ 1. Adamietta housei

2. Neoradina prasongi

3. Thiara scabra

4. Sermyla riqueti

5. Tarebia granifera

111

˜µ¦µŠš ¸É 9 (˜n°) ¨Îµ—´š ¸É œ·— °Š®°¥ ¦¼ž£µ¡ 6. Melanoides jugicostis

7. Melanoides tuberculata

Paracrostoma paludiformis dubiosa 8.

9. Paracrostoma paludiformis paludiformis

10. Paracrostoma pseudosulcospira pseudosulcospira

112

˜µ¦µŠš ¸É 9 (˜n°) ¨Îµ—´š ¸É œ·— °Š®°¥ ¦¼ž£µ¡ 11. Brotia (Brotia) costula costula

12. Brotia (Senckenbergia) wykoffi

13. Brotia (Brotia) microsculpta

14. Brotia (Brotia) maningi

113

˜µ¦µŠš ¸É 9 (˜n°) ¨Îµ—´š ¸É œ·— °Š®°¥ ¦¼ž£µ¡ 15. Brotia (Brotia) citrina

16. Brotia (Brotia) binodosa binodosa

17. Brotia (Brotia) baccata

114

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