A Model for Evaluation and Ranking of Human Resources Risks with an Intelligent Neuro-Fuzzy Approach (ANFIS) In National Iranian Gas Company
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Abstract:
The present study aimed to design a model of human resources risks assessment and ranking using the neuro-fuzzy approach as one of the methods of artificial intelligence in Iran national Gas Company. Three main steps were taken to achieve this goal: the first step was to identify the evaluation criteria that were achieved by literature reviews and the theoretical foundations of the research based on the opinion of the elites. The second step was human resources risks modeling using a neuro-fuzzy approach, which were formulated with two methods of subtractive clustering and grid partition regularization. In the third step, using the neuro-fuzzy system modeling, human resource ranking was performed. The results of ranking of human resource risks showed that Yazd province had the highest structural risks, Ilam province had the highest value risks and Khorasan Razavi province had the highest behavioral and contextual risks. The results of the overall evaluation also showed that human resources risks in Isfahan province hadthe least risks and Khorasan Razavi province hadthe highest human resources risks in Iran national Gas Company. The findings of this study can be considered as a comprehensive structure and a roadmap for managers to improve the formulation of HRM strategies.
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Journal title
volume 12 issue None
pages 95- 122
publication date 2020-12
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