Strategic Framework for ANFIS and BIM Use on Risk Management at Natural Gas Pipeline Project

Abstract

Risk management and assessment is a multi-criteria decision-making problem involving various factors, according to literature research and expert opinions. In order to establish effective models and resolve the relationship between these criteria’s; Researchers and Academics have presented a wide range of methods or models in the literature. In order to overcome the most strategic issue that affects the project performance scales, such as Risk Management, the most appropriate method and criterion selection is required. In this study; A case study conducted using the multi-criteria Adaptive Neuro Fuzzy Inference System (ANFIS), which provides the rating of 105 recorded risk types covering the design and construction processes. Combining the structures and advantages of adaptive networks with fuzzy inference methodology has shown that a more comprehensive and effective risk management and assessment made. It has been shown with Root mean square error (RMSE), mean absulate percantage error (MAPE) and R² performance indicators that it gives better results in artificial intelligence supported risk management or assessment created with Adaptive Neuro Fuzzy Inference System. The main contribution of this study; is the approach of artificial intelligence to evaluate and rate the risk correctly with hybrid learning method and then to obtain risk maps by integrating them into BIM as visual and linguistic term or pop-up expressions.