An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery
Researchers have been continuously trying to improve human performance with respect to Health, Safety and Environment (HSE) and ergonomics (hence HSEE). This study proposes an adaptive neural network (ANN) algorithm for measuring and improving job satisfaction among operators with respect to HSEE in...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
Elsevier Ltd
2011
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| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0950423011000234 http://hdl.handle.net/20.500.11937/49711 |
| _version_ | 1848758299572305920 |
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| author | Azadeh, A. Rouzbahman, M. Saberi, Morteza Mohammad Fam, I. |
| author_facet | Azadeh, A. Rouzbahman, M. Saberi, Morteza Mohammad Fam, I. |
| author_sort | Azadeh, A. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | Researchers have been continuously trying to improve human performance with respect to Health, Safety and Environment (HSE) and ergonomics (hence HSEE). This study proposes an adaptive neural network (ANN) algorithm for measuring and improving job satisfaction among operators with respect to HSEE in a gas refinery. To achieve the objectives of this study, standard questionnaires with respect to HSEE are completed by operators. The average results for each category of HSEE are used as inputs and job satisfaction is used as output for the ANN algorithm. Moreover, ANN is used to rank operators performance with respect to HSEE and job satisfaction. Finally, Normal probability technique is used to identify outlier operators. Moreover, operators with inadequate job satisfaction with respect to HSEE are identified. This would help managers to see if operators are satisfied with their jobs in the context of HSEE. This is the first study that introduces an integrated ANN algorithm for assessment and improvement of human job satisfaction with respect to HSEE program in complex systems. |
| first_indexed | 2025-11-14T09:41:47Z |
| format | Journal Article |
| id | curtin-20.500.11937-49711 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T09:41:47Z |
| publishDate | 2011 |
| publisher | Elsevier Ltd |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-497112017-03-15T22:56:34Z An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery Azadeh, A. Rouzbahman, M. Saberi, Morteza Mohammad Fam, I. Assessment Job satisfaction "Health safety and environment (HSE)" Artificial neural network Human operators Ergonomics Researchers have been continuously trying to improve human performance with respect to Health, Safety and Environment (HSE) and ergonomics (hence HSEE). This study proposes an adaptive neural network (ANN) algorithm for measuring and improving job satisfaction among operators with respect to HSEE in a gas refinery. To achieve the objectives of this study, standard questionnaires with respect to HSEE are completed by operators. The average results for each category of HSEE are used as inputs and job satisfaction is used as output for the ANN algorithm. Moreover, ANN is used to rank operators performance with respect to HSEE and job satisfaction. Finally, Normal probability technique is used to identify outlier operators. Moreover, operators with inadequate job satisfaction with respect to HSEE are identified. This would help managers to see if operators are satisfied with their jobs in the context of HSEE. This is the first study that introduces an integrated ANN algorithm for assessment and improvement of human job satisfaction with respect to HSEE program in complex systems. 2011 Journal Article http://hdl.handle.net/20.500.11937/49711 http://www.sciencedirect.com/science/article/pii/S0950423011000234 Elsevier Ltd restricted |
| spellingShingle | Assessment Job satisfaction "Health safety and environment (HSE)" Artificial neural network Human operators Ergonomics Azadeh, A. Rouzbahman, M. Saberi, Morteza Mohammad Fam, I. An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery |
| title | An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery |
| title_full | An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery |
| title_fullStr | An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery |
| title_full_unstemmed | An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery |
| title_short | An adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to HSE and ergonomics program: The case of a gas refinery |
| title_sort | adaptive neural network algorithm for assessment and improvement of job satisfaction with respect to hse and ergonomics program: the case of a gas refinery |
| topic | Assessment Job satisfaction "Health safety and environment (HSE)" Artificial neural network Human operators Ergonomics |
| url | http://www.sciencedirect.com/science/article/pii/S0950423011000234 http://hdl.handle.net/20.500.11937/49711 |