Application of Expert System Technology for the Decontamination of Water Distribution Networks
Decontamination of water distribution networks (WDNs) is a difficult process to conduct. Creation of an effective approach necessitates integrating rules and requirements from diverse knowledge domains in such a way that the operational goals are achieved with minimally available situational information. To date, there has been a limited amount of work in applying expert systems in this problem domain. This research 1) identifies and assimilates the knowledge necessary for WDN decontamination; and 2) evaluates the relative benefits of forward and backward chaining inferential logic in WDN decontamination. Based on the results of this analysis, we developed a backward-chaining prototype expert system for WDN decontamination. The system provides reasoning routines and recommendations on the type of event and consequences on the water operator's clients, the public in general, the environment, and the potential hazards from the resulting chemical interactions.
Copyright (c) 2019 Gary Moynihan, Xiaoyin Zhang, Andrew Ernest, Joseph Gutenson
This work is licensed under a Creative Commons Attribution 4.0 International License.