Approximate cost estimating model for river facility construction based on case-based reasoning with genetic algorithms

Abstract

The approximate construction cost estimation at the planning stage is very important in that it significantly affects the plan of the construction project regarding its size, budget, and construction time. However, systematic approaches for the approximate cost estimation of river facility construction at the planning stage have been rarely established. This study proposes an approximate cost estimating model for irrigation-type river facility construction at the planning stage, based on Case-Based Reasoning (CBR) with Genetic Algorithms (GA). In the development of the model, the 92 historical cases of irrigation-type river facility construction were used to compile the database of the CBR model and the 79 historical cases were used to determine the attribute weights for the model with GA. The 6 main attributes that are the only input factors required for the proposed model include embankment extension, revetment extension, freeboard, number of drain gates, number of drain pipes, and slope covering material. The results of the verification of the proposed model with the 18 historical cases indicate that the proposed model proposed is satisfactory in its application for approximate cost estimation of irrigation-type river facility construction at the planning stage. It is expected that the proposed model based on CBR with GA will contribute to easier and more convenient estimation on the approximate costs of river facility construction at the planning stage.