Workplace safety risk assessment model based on fuzzy regression
Regulating safety and health in a workplace is crucial for any industry. It makes measuring a level of risk to characterize hazards in a workplace is a necessary. A systematic risk assessment in a workplace is capable to evaluate the level of risk which might occur. The assessment of risk in workpla...
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| Format: | Article |
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American Scientific Publishers
2011
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| Online Access: | http://eprints.uthm.edu.my/5665/ |
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| _version_ | 1833417908345110528 |
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| author | Arbaiy, Nureize Ab Rahman, Hamijah Mohd Salikon, Mohd Zaki Pei, Chun Lin |
| author_facet | Arbaiy, Nureize Ab Rahman, Hamijah Mohd Salikon, Mohd Zaki Pei, Chun Lin |
| author_sort | Arbaiy, Nureize |
| building | UTHM Library |
| collection | Institutional Repository |
| content_provider | Universiti Tun Hussein Onn Malaysia |
| content_source | UTHM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Regulating safety and health in a workplace is crucial for any industry. It makes measuring a level of risk to characterize hazards in a workplace is a necessary. A systematic risk assessment in a workplace is capable to evaluate the level of risk which might occur. The assessment of risk in workplace regularly is performed by several identified attributes. At present, quantitative risk assessment uses crisp value in its evaluation. However, risk assessment process is exposed to uncertain information, due to human evaluation which uses linguistic value and is difficult to translate into precise numerical value. It makes the risk assessment process in workplace is imprecise. Thus, a robust fuzzy regression is introduced in this paper to determine the fuzzy weights of assessment attribute and build a robust fuzzy assessment model. This is important to identify the relationship among attributes, and helps the examiners to conduct a proper assessment in uncertain environment. A triangular fuzzy number is used to present the fuzzy judgment. An explanatory example is included to show the working procedure. The result indicates that the proposed model is beneficial to facilitate the decision model in evaluating risk, and specify excellent choice under the presence of uncertainty. |
| format | Article |
| id | my.uthm.eprints-5665 |
| institution | Universiti Tun Hussein Onn Malaysia |
| publishDate | 2011 |
| publisher | American Scientific Publishers |
| record_format | eprints |
| spelling | my.uthm.eprints-56652022-01-20T02:36:03Z http://eprints.uthm.edu.my/5665/ Workplace safety risk assessment model based on fuzzy regression Arbaiy, Nureize Ab Rahman, Hamijah Mohd Salikon, Mohd Zaki Pei, Chun Lin HD58 Location of industry HD61 Risk in industry. Risk management Regulating safety and health in a workplace is crucial for any industry. It makes measuring a level of risk to characterize hazards in a workplace is a necessary. A systematic risk assessment in a workplace is capable to evaluate the level of risk which might occur. The assessment of risk in workplace regularly is performed by several identified attributes. At present, quantitative risk assessment uses crisp value in its evaluation. However, risk assessment process is exposed to uncertain information, due to human evaluation which uses linguistic value and is difficult to translate into precise numerical value. It makes the risk assessment process in workplace is imprecise. Thus, a robust fuzzy regression is introduced in this paper to determine the fuzzy weights of assessment attribute and build a robust fuzzy assessment model. This is important to identify the relationship among attributes, and helps the examiners to conduct a proper assessment in uncertain environment. A triangular fuzzy number is used to present the fuzzy judgment. An explanatory example is included to show the working procedure. The result indicates that the proposed model is beneficial to facilitate the decision model in evaluating risk, and specify excellent choice under the presence of uncertainty. American Scientific Publishers 2011 Article PeerReviewed Arbaiy, Nureize and Ab Rahman, Hamijah and Mohd Salikon, Mohd Zaki and Pei, Chun Lin (2011) Workplace safety risk assessment model based on fuzzy regression. Advanced Science Letters, 4. pp. 400-407. ISSN 1936-6612 |
| spellingShingle | HD58 Location of industry HD61 Risk in industry. Risk management Arbaiy, Nureize Ab Rahman, Hamijah Mohd Salikon, Mohd Zaki Pei, Chun Lin Workplace safety risk assessment model based on fuzzy regression |
| title | Workplace safety risk assessment model based on fuzzy regression |
| title_full | Workplace safety risk assessment model based on fuzzy regression |
| title_fullStr | Workplace safety risk assessment model based on fuzzy regression |
| title_full_unstemmed | Workplace safety risk assessment model based on fuzzy regression |
| title_short | Workplace safety risk assessment model based on fuzzy regression |
| title_sort | workplace safety risk assessment model based on fuzzy regression |
| topic | HD58 Location of industry HD61 Risk in industry. Risk management |
| url | http://eprints.uthm.edu.my/5665/ |
| url_provider | http://eprints.uthm.edu.my/ |