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Workplace safety risk assessment model based on fuzzy regression

Arbaiy, Nureize and Ab Rahman, Hamijah and Mohd Salikon, Mohd Zaki and Lin, Pei Chun (2018) Workplace safety risk assessment model based on fuzzy regression. Advanced Science Letters, 24 (3). pp. 1656-1659. ISSN 19366612

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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.

Item Type: Article
Uncontrolled Keywords: Fuzzy number; fuzzy regression; risk assessment; uncertainty
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: Faculty of Computer Science and Information Technology > Department of Software Engineering
Depositing User: Mr. Mohammad Shaifulrip Ithnin
Date Deposited: 31 Jul 2019 00:58
Last Modified: 31 Jul 2019 00:58
URI: http://eprints.uthm.edu.my/id/eprint/11358
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