A probabilistic reasoning-based decision support system for selection of remediation technologies for petroleum-contaminated sites

Authors:
L. He;C. W. Chan;G. H. Huang;G. M. Zeng
Affiliations:
Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2;Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2;Faculty of Engineering, University of Regina, Regina, Saskatchewan, Canada S4S 0A2;College of Environmental Science and Engineering, Hunan University, Changsha, Hunan, China 410082
Venue:
Expert Systems with Applications: An International Journal
Year:
2006

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Abstract

Selection of remediation technologies for petroleum-contaminated sites is difficult given the large number of technologies available and inherent uncertainties involved in the selection process. In this paper, we explore the use of an inexact algorithm for probability reasoning for dealing with the uncertainties involved in the problem. By incorporating domain knowledge as well as the stochastic uncertainty, a probabilistic rule-based decision support system (PDSS) has been developed to support the decision making process. The system has been applied to two case studies, in which the best option of remediation technology can be determined according to calculated probability values. In comparison to deterministic and fuzzy decision support systems, the PDSS can provide a recommendation together with a measure on the reliability or degree to which the recommended decision can be trusted.