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Interpreting fuzzy cognitive maps (FCMs) using fuzzy measures to evaluate water quality failures in distribution networks

From National Research Council Canada

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Affiliation
  1. National Research Council of Canada. NRC Institute for Research in Construction
FormatText, Article
ConferenceJoint International Conference on Computation in Civil and Building Engineering (ICCCBE XI): 14 June 2006, Montreal, QC.
Subjectfuzzy cognitive maps (FCMs), fuzzy measures, water distribution networks, water quality failure; Water quality
Abstract
Numerous factors affect water quality in the distribution networks and the interactions amongst them are complex and often not well understood. Water quality failures in distribution systems are scarce, which make statistically significant generalizations difficult. However, the rarity of water quality failures belies their seriousness, since each failure indicates the potential for harmful public health effects and increased public mistrust and complaints. In such data-sparse circumstances, expert knowledge and judgment can serve as an alternative source of information. Fuzzy cognitive map (FCM) is, as the name suggests, a map of interconnected factors, each of which can interact with some or all of the others, to represent a specific process or behaviour of a network or system. A predictive model based on a FCM is a plausible way to comprehend ill-defined and complex relationships that govern water quality in the distribution network. The proposed FCM model is defined in two levels to help reduce the complexity of the system. At the modular (lower) level, rule-based FCMs are proposed for various deterioration mechanisms, which contribute to water quality failure in distribution networks. At supervisory (higher) level, a FCM is proposed, which employs fuzzy measures to interpret activation signals generated from modular FCMs to predict various types of water quality failures in distribution networks.
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  • Joint International Conference on Computation in Civil and Building Engineering (ICCCBE XI) [Proceedings] (14 June 2006): 1–10.
LanguageEnglish
Peer reviewedYes
NRC numberNRCC 45601
NRC-IRC-18089
NPARC number20377985
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Record identifiera7096ec6-6cea-47e6-b813-1618405bcdde
Record created2012-07-24
Record modified2020-04-22
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