Modeling contaminant intrusion in water distribution networks: A new similarity-based DST method
Contaminant intrusion in a water distribution network is a complex but a commonly observed phenomenon, which depends on three elements  a pathway, a driving force and a contamination source. However, the data on these elements are generally incomplete, non-specific and uncertain. In an earlier work, Sadiq, Kleiner, and Rajani (2006) have successfully applied traditional DempsterShafer theory (DST) to estimate the risk of contaminant intrusion in a water distribution network based on limited uncertain information. However, the method used for generating basic probability assignment (BPA) was not very flexible, and did not handle and process uncertain information effectively. In this paper, a more pragmatic method is proposed that utilizes soft computing flexibility to generate BPAs from uncertain information. This paper compares these two methods through numerical examples, and demonstrates the efficiency and effectiveness of modified method.
water distribution networks dempstershafer theory risk of contaminant intrusion fuzzy set theory similarity measure uncertainty