<i>Water Expert</i>: a conceptualized framework for development of a rule-based decision support system for distribution system decontamination

Author:

Gutenson J. L.ORCID,Ernest A. N. S.,Fattic J. R.,Ormsbee L. E.,Oubeidillah A. A.,Zhang X.

Abstract

Abstract. Significant drinking water contamination events pose a serious threat to public and environmental health. Water utilities often must make timely, critical decisions without evaluating all facets of the incident. The data needed to enact informed decisions are inevitably dispersant and disparate, originating from policy, science, and heuristic contributors. Water Expert is a functioning hybrid decision support system (DSS) and expert system framework that emphasizes the meshing of parallel data structures in order to expedite and optimize the decision pathway. Delivered as a thin-client application through the user's web browser, Water Expert's extensive knowledgebase is a product of inter-university collaboration that methodically pieced together system decontamination procedures. Decontamination procedures are investigated through consultation with subject matter experts, literature review, and prototyping with stakeholders. This paper discusses the development of Water Expert, analyzing the development process underlying the DSS and the system's existing architecture specifications. Water Expert constitutes the first system to employ a combination of deterministic and heuristic models which provide decontamination solutions for water distribution systems. Results indicate that the decision making process following a contamination event is a multi-disciplinary effort. This contortion of multiple inputs and objectives limit the ability of the decision maker to find optimum solutions without technological intervention.

Publisher

Copernicus GmbH

Subject

Pollution,Water Science and Technology,Civil and Structural Engineering

Reference74 articles.

1. Agency for Toxic Substances & Disease Registry (ATSDR): http://www.atsdr.cdc.gov/mrls/index.asp (last access: 30 March 2014), 2013.

2. Ahn, B. S., Cho, S. S., and Kim, C. Y.: The integrated methodology of rough set theory and artificial neural network for business failure prediction, Expert Syst. Appl., 18, 65–74, https://doi.org/10.1016/S0957-4174(99)00053-6, 2000.

3. Alva-Lizarraga, S. and Johnson, T. G.: A dynamic demand driven, supply constrained input output approach to modeling economic impacts of water disruption events, 2012 Conference Proceedings, Mid-Continent Regional Science Association, Ottawa, Canada, 6–8 June 2012, 159–177, 2012.

4. American Water Works Association (AWWA) and Economic and Engineering Services, Inc.: Permeation and leaching, US Environmental Protection Agency, Washington, DC, 22 pp., 2002.

5. Bahrammirzaee, A.: A comparative survey of artificial intelligence applications in finance: Artificial neural networks, expert system and hybrid intelligent systems, Neural Comput. Appl., 19, 1165–1195, https://doi.org/10.1007/s00521-010-0362-z, 2010.

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3