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Construction project risk assessment by using adaptive-network-based fuzzy inference system: An empirical study

  • Construction Management
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Abstract

Managers require a good understanding about the nature of risks involved in a construction project because the duration, quality, and budget of projects can be affected by these risks. Thus, the identification of risks and the determination of their priorities in every phase of the construction can assist project managers in planning and taking proper actions against those risks. Therefore, prioritizing risks via the risk factors can increase the reliability of success. In this research, first the risks involved in construction projects has been identified and arranged in a systematic hierarchical structure. Next, based on the obtained data an Adaptive Neuro-Fuzzy Inference System (ANFIS) has been designed for the evaluation of project risks. In addition, a stepwise regression model has also been designed and its results are compared with the results of ANFIS. The results show that the ANFIS models are more satisfactory in the assessment of construction projects risks. Our proposed methodology can be applied by managers of construction projects and practitioners to assess of risk factor of construction projects in a proper manner.

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Authors and Affiliations

  1. Master of Science, Faculty of Industrial and Mechanical Engineering, Islamic Azad University, Qazvin Branch, Qazvin, Iran

    Mehdi Ebrat

  2. Engineering Dept., Central Connecticut State University, New Briatin, Connecticut, 06050, USA

    Reza Ghodsi

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  1. Mehdi Ebrat
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  2. Reza Ghodsi
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Correspondence to Mehdi Ebrat.

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Ebrat, M., Ghodsi, R. Construction project risk assessment by using adaptive-network-based fuzzy inference system: An empirical study. KSCE J Civ Eng 18, 1213–1227 (2014). https://doi.org/10.1007/s12205-014-0139-5

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  • DOI: https://doi.org/10.1007/s12205-014-0139-5

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