Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Construction project risk assessment by using adaptive-network-based fuzzy inference system: An empirical study
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.
Construction project risk assessment by using adaptive-network-based fuzzy inference system: An empirical study
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.
Construction project risk assessment by using adaptive-network-based fuzzy inference system: An empirical study
Ebrat, Mehdi (Autor:in) / Ghodsi, Reza (Autor:in)
KSCE Journal of Civil Engineering ; 18 ; 1213-1227
01.06.2014
15 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
Forecasting project success in the construction industry using adaptive neuro-fuzzy inference system
| Taylor & Francis Verlag | 2024
A proposal for construction project risk assessment using fuzzy logic
| Online Contents | 2000