Forecasting Techniques in Construction Industry: Earned Value Indicators and Performance Models
Scientifi c Review – Engineering and Environmental Sciences (2020), 29 (2), 234–243 Sci. Rev. Eng. Env. Sci. (2020), 29 (2) Przegląd Naukowy – Inżynieria i Kształtowanie Środowiska (2020), 29 (2), 234–243 Prz. Nauk. Inż. Kszt. Środ. (2020), 29 (2) http://iks.pn.sggw.pl DOI 10.22630/PNIKS.2020.29.2.20 Firas Kh. JABER1, Nidal A. JASIM2, Faiq M.S. Al-ZWAINY3 1 Middle Technical University, Electrical Engineering Technical College 2 University of Diyala, College of Engineering 3 Al-Nahrain University, College of Engineering Forecasting techniques in construction industry: earned value indicators and performance models Key words: Machine Learning Regression other industries by its many risks, and its Techniques (MLRT), earned value indexes, projects always suffer from the problems SPI, CPI, and TCPI of delay in implementation and increase in cost in most countries of the world. Among the most important characteris- Introduction tics of the construction industry (Myers, 2005): The construction industry is an im- 1. The nature of its product is unique, portant industry for any government each project differs from the other, due to its direct association with the im- and the temporary of each project is plementation of the goals and policies limited in duration and location, with of the government in various fi elds of the completion of the project, the concern to the citizen in terms of educa- equipment and labor will be trans- tion, health, housing and other facilities ferred to another project in another and services. The construction industry place. is also one of the broad and important 2. The nature of work within a single sectors of any country’s economy, and it project is fragmented, as several dif- is one of the main engines that govern- ferent parties separate and separate ments resort to move the economy and to complete the project.
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