Development an ANFIS model for human resource risk analysis and management in construction projects

The role of human resources in reducing human resource risks and, consequently, organizational risks and organizational profitability, is an undeniable and very important role, and the role of human resources is something beyond administrative and office roles, which unfortunately this view There is a role for human resource management in most project-oriented organizations and so far the risk of strategic human resource actions, especially in the country's manufacturing industry projects has not been systematically assessed.The present paper aimed to identify the risks affecting human resource management in construction projects and provide an integrated model based on Adaptive Network-based Fuzzy Inference System (ANFIS) for risk assessment. By determining the probability, severity and rate of occurrence of risks, a total of 9 risk factors including (1) lack of maturity and knowledge of specialized staff, (2) job stress, (3) employee motivation, (4) lack of attention to the management process Performance and feedback, (5) lack of financial resources to reward innovative activities, (6) inappropriate payment policies, (7) discriminatory performance between human resources, (8) lack of technical knowledge and skills, and (9) lack of Possession of trust-building skills among employees was identified as critical (unauthorized) risks. The results of correlation coefficient criteria to determine the error value of the two methods presented showed that random data had a higher correlation coefficient than the actual data of experts and the results were satisfactory with high accuracy. Also, qualitative and quantitative analysis of risks by ANFIS method and based on experts' opinions and random data showed that if the risks are not available in projects that are being implemented for the first time or access to the required number of experts, by adopting and selecting appropriate random input data. Fuzzy intervals, instead of experts' opinions and their analysis by ANFIS method, obtain acceptable results.