In this paper we describe how an evidential-reasoner can be used as a component of risk assessment of engineering projects using a direct way of reasoning. Guan & Bell (1991) introduced this method by using the mass functions to express rule strengths. Mass functions are also used to express data strengths. The data and rule strengths are combined to get a mass distribution for each rule; i.e., the first half of our reasoning process. Then we combine the prior mass and the evidence from the different rules; i.e., the second half of the reasoning process. Finally, belief intervals are calculated to help in identifying the risks. We apply our evidential-reasoner on an engineering project and the results demonstrate the feasibility and applicability of this system in this environment.
|Title of host publication||Intelligent Data Engineering and Automated Learning– IDEAL 2006|
|Number of pages||8|
|Publication status||Published - 2006|
|Name||Lecture Notes in Computer Science|
Khokhar, R. H., Bell, D., Guan, J. W., & Wu, Q. (2006). Knowledge-based risk assessment under uncertainty in engineering projects. In Intelligent Data Engineering and Automated Learning– IDEAL 2006 (Vol. 4224, pp. 1296-1303). (Lecture Notes in Computer Science; Vol. 4224). https://doi.org/10.1007/11875581_154