Health, Safety, Environment and Ergonomic Improvement in Energy Sector Using an Integrated Fuzzy Cognitive Map–Bayesian Network Model

Pourreza, P; Saberi, M; Azadeh, A; Chang, E; Hussain, O

Health, Safety, Environment and Ergonomic Improvement in Energy Sector Using an Integrated Fuzzy Cognitive Map–Bayesian Network Model

Pourreza, P Saberi, M

Azadeh, A Chang, E Hussain, O

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Publication Type:: Journal Article
Citation:: International Journal of Fuzzy Systems, 2018, 20 (4), pp. 1346 - 1356
Issue Date:: 2018-04-01

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Field	Value	Language
dc.contributor.author	Pourreza, P	en_US
dc.contributor.author	Saberi, M https://orcid.org/0000-0002-5168-2078	en_US
dc.contributor.author	Azadeh, A	en_US
dc.contributor.author	Chang, E	en_US
dc.contributor.author	Hussain, O	en_US
dc.date.issued	2018-04-01	en_US
dc.identifier.citation	International Journal of Fuzzy Systems, 2018, 20 (4), pp. 1346 - 1356	en_US
dc.identifier.issn	1562-2479	en_US
dc.identifier.uri	http://hdl.handle.net/10453/133051
dc.description.abstract	© 2018, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. Health, safety, environment and ergonomics (HSEE) are important factors for any organization. In fact, organizations always have to assess their compliance in these factors to the required benchmarks and take proactive actions to improve them if required. In this paper, we propose a fuzzy cognitive map–Bayesian network (BN) model in order to assist organizations in undertaking this process. The fuzzy cognitive map (FCM) method is used for constructing graphical models of BN to ascertain the relationships between the inputs and the impact which they will have on the quantified HSEE. Using the notion of Fuzzy logic assists us to work with humans and their linguistic inputs in the process of experts’ opinion solicitation. The noisy-OR method and the EM are used to ascertain the conditional probability between the inputs and quantifying the HSEE value. Using this, we find out that the most influential input factor on HSEE quantification which can then be managed for improving an organization’s compliance to HSEE. Finding the same influential input factor in both BN models which are based on the noisy-OR method and EM demonstrate how FCM is useful in constructing a reliable BN model. Leveraging the power of Bayesian network in modelling HSEE and augmenting it with FCM is the main contribution of this research work which opens the new line of research in the area of HSE management.	en_US
dc.relation.ispartof	International Journal of Fuzzy Systems	en_US
dc.relation.isbasedon	10.1007/s40815-018-0461-z	en_US
dc.rights	info:eu-repo/semantics/openAccess
dc.subject.classification	Artificial Intelligence & Image Processing	en_US
dc.title	Health, Safety, Environment and Ergonomic Improvement in Energy Sector Using an Integrated Fuzzy Cognitive Map–Bayesian Network Model	en_US
dc.type	Journal Article
utslib.citation.volume	4	en_US
utslib.citation.volume	20	en_US
utslib.for	1605 Policy and Administration	en_US
utslib.for	0802 Computation Theory and Mathematics	en_US
utslib.for	0102 Applied Mathematics	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
utslib.copyright.status	open_access	*
pubs.issue	4	en_US
pubs.publication-status	Published	en_US
pubs.volume	20	en_US

Abstract:

© 2018, Taiwan Fuzzy Systems Association and Springer-Verlag GmbH Germany, part of Springer Nature. Health, safety, environment and ergonomics (HSEE) are important factors for any organization. In fact, organizations always have to assess their compliance in these factors to the required benchmarks and take proactive actions to improve them if required. In this paper, we propose a fuzzy cognitive map–Bayesian network (BN) model in order to assist organizations in undertaking this process. The fuzzy cognitive map (FCM) method is used for constructing graphical models of BN to ascertain the relationships between the inputs and the impact which they will have on the quantified HSEE. Using the notion of Fuzzy logic assists us to work with humans and their linguistic inputs in the process of experts’ opinion solicitation. The noisy-OR method and the EM are used to ascertain the conditional probability between the inputs and quantifying the HSEE value. Using this, we find out that the most influential input factor on HSEE quantification which can then be managed for improving an organization’s compliance to HSEE. Finding the same influential input factor in both BN models which are based on the noisy-OR method and EM demonstrate how FCM is useful in constructing a reliable BN model. Leveraging the power of Bayesian network in modelling HSEE and augmenting it with FCM is the main contribution of this research work which opens the new line of research in the area of HSE management.

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http://hdl.handle.net/10453/133051