A novel regression prediction model for structural engineering applications

Jeng-Wen Lin, Cheng-Wu Chen and Ting-Chang Hsu

Abstract

Recently, artificial intelligence tools are most used for structural engineering and mechanics. In order to predict reserve prices and prices of awards, this study proposed a novel regression prediction model by the intelligent Kalman filtering method. An artificial intelligent multiple regression model was established using categorized data and then a prediction model using intelligent Kalman filtering. The rather precise construction bid price model was selected for the purpose of increasing the probability to win bids in the simulation example.

Key Words

construction project and management; intelligent fuzzy regression; Kalman filtering; prediction model

Address

Jeng-Wen Lin: Department of Civil Engineering, Feng Chia University, Taichung 407, Taiwan, R.O.C. Cheng-Wu Chen: Department of Maritime Information and Technology, National Kaohsiung Marine University, Kaohsiung, Taiwan, R.O.C.; Global Earth Observation and Data Analysis Center, National Cheng Kung University, Tainan, Taiwan 701, R.O.C. Ting-Chang Hsu: Department of Civil Engineering, Feng Chia University, Taichung 407, Taiwan, R.O.C.

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