Designing Fuzzy Inference System by Learning from Training Samples to Measure the Participation of Operational Staff in the Health of Workplace
To achieve the highest level of health in organizations, there is a need to create a proper space for active participation of staff. To enable this partnership, organizations need tools to measure participation to determine deviations, in order to revise their programs. This research aimed to design...
| Main Authors: | , , |
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| Format: | Article |
| Language: | fas |
| Published: |
University of Tehran
2016-12-01
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| Series: | Journal of Information Technology Management |
| Subjects: | |
| Online Access: | https://jitm.ut.ac.ir/article_59952_a5e2f84c6395288f2bbd6db3db218249.pdf |
| Summary: | To achieve the highest level of health in organizations, there is a need to create a proper space for active participation of staff. To enable this partnership, organizations need tools to measure participation to determine deviations, in order to revise their programs. This research aimed to design a system for measuring employee participation in workplace health regardless of the estimation of non-linear relationships between the effective variables. For this purpose, we designed a Fuzzy Inference System. Employees' participation scores and predisposing factors involved in health respectively, considered as output and input of the system. Rules have been created by using modified CT08 method based on training samples. In the end, we created 17 rules and the system was tested with 5 prototypes. It should be noted that the accuracy rate was 92.3 percent. The researchers also suggested changes in calculation of accuracy rate which made the rate more realistic. |
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| ISSN: | 2008-5893 2423-5059 |