Decision making for contractor insurance deductible using the evolutionary support vector machines inference model

Authors:
Min-Yuan Cheng;Hsien-Sheng Peng;Yu-Wei Wu;Yi-Hung Liao
Affiliations:
Department of Construction Engineering, National Taiwan University of Science and Technology, Taiwan;Ecological and Hazard Mitigation Engineering Research Center, National Taiwan University of Science and Technology, Taiwan;Department of Construction Engineering, National Taiwan University of Science and Technology, Taiwan;Department of Construction Engineering, National Taiwan University of Science and Technology, Taiwan
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Loss risk during the course of a construction project may be described in terms of frequency (i.e., loss frequency) and severity (i.e., loss severity). This study focused on improving the methodology used to evaluate loss risk. The authors first identified the common attributes of building construction project loss through a review of the literature and interviews with experts. Objective factors adequate to describe loss attributes were selected as model inputs. The loss prediction model was created using the evolutionary support vector machine inference model (ESIM) and deployed to evaluate loss frequency and loss severity. This research combined the deductible efficient frontier curve with the indifference curve of risk versus insurance cost, and developed criteria for optimal insurance deductible decision making.