Construction Cost Estimation for Government Building Using Prediction Modeling Techniques

Abstract

Due to the contraction of the domestic construction industry, "construction auction competition accuracy" is required for bidding on construction tenders - to prevent huge revenue losses due to low bids in the auction process. This construction bidding accuracy is required of both the private and public sectors. However, before the auction, every bidder has to estimate construction prices before placing their bid. There are 2 popular methods for estimating construction costs. approximate estimate, or a detailed estimate. The strength of estimating a construction cost quickly is that you get a fast estimate. However, the results might not be accurate. On the other hand, doing a detailed plan and takes lots of time. Due to both estimation methods having inherent disadvantages, it seems absolutely necessary to create an accurate prediction model for construction cost estimation in government buildings. That way, We don’t have to rely on inaccurate bidding processes. We will use linear regression analysis instead. There are 11 variables we can look at in order to efficiently decide how much a building might cost to construct. These are as followed: 1) Usable area 2) Average perimeter 3) Average inter-floor height 4) Building height 5) Number of floors 6) Roof area 7) Bathroom size 8) Ground floor area 9) Open space 10) Type of roofing material 11) Type of floor structure. By taking all of these factors into consideration, we can accurately gauge the cost of constructing a government building, without having to rely on bidders, who struggle to efficiently and accurately estimate these prices!