 Integration of interpretive structural modelling with Bayesian network for biodiesel performance analysisZaman Sajid, Faisal Khan and Yan Zhang Renewable Energy, 2017, vol. 107, issue C, 194-203 Abstract: The performance of a biodiesel system can be affected by varied risk factors. The numbers of such risk factors are large and their interdependencies are vague and complex. The purpose of this study is to define relationships among such risk factors and integrate them with an objective risk analysis approach. In the present study, an interpretive structural modelling (ISM) approach was used to identify relationships among risk factors while a Bayesian Network (BN) approach was employed to define the strength of dependence and conduct a risk analysis. The results indicate that among 25 risk factors, operational safety is a key biodiesel performance factor. The analysis also highlights that the impacts of occupational health and natural resources depletion are strongly dependent on environmental parameters. Occupational health is also strongly dependent on plant safety. The results show that the interdependency between occupational health and natural resources depletion is weak. Keywords: Biodiesel system; Risk analysis; Safety analysis; Interpretive structural modelling; Dependence analysis (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:107:y:2017:i:c:p:194-203 DOI: 10.1016/j.renene.2017.01.058 Access Statistics for this article Renewable Energy is currently edited by Soteris A. Kalogirou and Paul Christodoulides More articles in Renewable Energy from Elsevier |
Is your work missing from RePEc? Here is how to contribute.
Questions or problems? Check the EconPapers FAQ or send mail to .
EconPapers is hosted by the
School of Business at Örebro University.