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...

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Main Authors: Saeed Malekinejad, Ahmad Tavakoli, Naser Motahari
Format: Article
Language:fas
Published: University of Tehran 2016-12-01
Series:Journal of Information Technology Management
Subjects:
Online Access:https://jitm.ut.ac.ir/article_59952_a5e2f84c6395288f2bbd6db3db218249.pdf
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spelling doaj-bd2a56feacb44c7d96d1c78674821aed2020-11-25T00:09:29ZfasUniversity of TehranJournal of Information Technology Management 2008-58932423-50592016-12-018479181010.22059/jitm.2016.5995259952Designing Fuzzy Inference System by Learning from Training Samples to Measure the Participation of Operational Staff in the Health of WorkplaceSaeed Malekinejad0Ahmad Tavakoli1Naser Motahari2MSc. Student, Ferdowsi University of Mashhad, Mashhad, IranAssistant Prof., in Management, Faculty of Economic & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, IranAssistant Prof., in Management, Faculty of Economic & Administrative Sciences, Ferdowsi University of Mashhad, Mashhad, IranTo 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.https://jitm.ut.ac.ir/article_59952_a5e2f84c6395288f2bbd6db3db218249.pdffuzzy inference systemoperational employee participationparticipation measurementworkplace health
collection DOAJ
language fas
format Article
sources DOAJ
author Saeed Malekinejad
Ahmad Tavakoli
Naser Motahari
spellingShingle Saeed Malekinejad
Ahmad Tavakoli
Naser Motahari
Designing Fuzzy Inference System by Learning from Training Samples to Measure the Participation of Operational Staff in the Health of Workplace
Journal of Information Technology Management
fuzzy inference system
operational employee participation
participation measurement
workplace health
author_facet Saeed Malekinejad
Ahmad Tavakoli
Naser Motahari
author_sort Saeed Malekinejad
title Designing Fuzzy Inference System by Learning from Training Samples to Measure the Participation of Operational Staff in the Health of Workplace
title_short Designing Fuzzy Inference System by Learning from Training Samples to Measure the Participation of Operational Staff in the Health of Workplace
title_full Designing Fuzzy Inference System by Learning from Training Samples to Measure the Participation of Operational Staff in the Health of Workplace
title_fullStr Designing Fuzzy Inference System by Learning from Training Samples to Measure the Participation of Operational Staff in the Health of Workplace
title_full_unstemmed Designing Fuzzy Inference System by Learning from Training Samples to Measure the Participation of Operational Staff in the Health of Workplace
title_sort designing fuzzy inference system by learning from training samples to measure the participation of operational staff in the health of workplace
publisher University of Tehran
series Journal of Information Technology Management
issn 2008-5893
2423-5059
publishDate 2016-12-01
description 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.
topic fuzzy inference system
operational employee participation
participation measurement
workplace health
url https://jitm.ut.ac.ir/article_59952_a5e2f84c6395288f2bbd6db3db218249.pdf
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