COMPARATIVE ANALYSIS OF MACHINE LEARNING TECHNIQUES USED IN CONSTRUCTION SITES: A SURVEY

Authors

  • Mohammad Kabir Yaqubi ME Research Scholar, Civil Engineering Department, Chandigarh University
  • Sandeep Salhotra Professor, Civil Engineering Department, Chandigarh University, Punjab, India

Keywords:

Construction sites, Cost, Time, Quality, Artificial Intelligence, ANN, SVM, GA, ACO.

Abstract

Construction Management (CM) should deal with a number of uncertainties related to Time, Cost, Quality, and Safety and so on. Such uncertainties make the entire construction process much unacceptable. Hence there is a use of artificial intelligence came into purview to solve the problem in an effective way. Cost estimation is the most important preliminary process in any construction project. Therefore, construction cost estimation has the lion’s share of the research effort in construction management. In this paper, we have analyzed and studied proposals for construction cost estimation for the last 10 years. From the research it has been observed that different researchers have worked on cost estimation using artificial intelligence schemes. It is highlighted that the researchers used mostly SVM, ANN and GA as an artificial intelligence techniques that helps to find an appropriate solution to the given construction problem. From the analysis it has been examine that SVM perform well as compared to other existing techniques.

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Published

2021-11-22

How to Cite

Yaqubi, M. K., & Salhotra, S. (2021). COMPARATIVE ANALYSIS OF MACHINE LEARNING TECHNIQUES USED IN CONSTRUCTION SITES: A SURVEY. International Journal of Technical Innovation in Modern Engineering & Science, 5(1), 387–394. Retrieved from https://ijtimes.com/index.php/ijtimes/article/view/2273