Possibilistic regression analysis of influential factors in the planning and implementation of Occupational Health and Safety management systems

Azizul Azhar Ramli, Junzo Watada, Witold Pedrycz

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    The code of Occupational Health and Safety (OHS) is an important regulation to improve the on-the-job safety of employees. Several factors affect the planning and implementation of OHS management systems (OHSMS). The evaluation of OHS practice is the most important component when building a safety environment policy for employees and administration. Begin aware of subjective nature of factors affecting OHS and the use of statistical method, it becomes controversial as to a way of handling this type of survey data. This research presents a combination of possibilistic regression analysis with a convex hull approach to analyze the fitting factors that impact good practices of OHS. In addition, selected samples of data could be represented as fuzzy sets. This study offers an alternative platform to evaluate influential factors being used towards a successful implementation of the OHS policy.

    Original languageEnglish
    Title of host publication2010 IEEE World Congress on Computational Intelligence, WCCI 2010
    DOIs
    Publication statusPublished - 2010
    Event2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - Barcelona
    Duration: 2010 Jul 182010 Jul 23

    Other

    Other2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010
    CityBarcelona
    Period10/7/1810/7/23

    ASJC Scopus subject areas

    • Artificial Intelligence
    • Computational Theory and Mathematics

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