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Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/18689
Title: Integrating empirical and heuristic knowledge in a KBS to approach stream eutrophication
Authors: Llorens, Esther; Comas, J.; Martí, Eugènia; Riera, Joan L.; Sabater, Francesc
Keywords: Eutrophication
Knowledge-based system
Water quality
Issue Date: 24-Sep-2009
Publisher: Elsevier
Citation: Ecological Modelling, 2009. 220(18): p. 2162-2172.
Abstract: The nutrient enrichment of rivers and its consequences are among the most severe water quality problems in Europe, causing eutrophication and other problems. The decision-making processes involved in the management of these problems require extensive human expertise from people who deal directly with day-to-day stream problems, as well as empirical knowledge based on scientific research. This means that eutrophication is a complex problem, the optimal management of which requires an integrated and multidisciplinary approach. This approach can be taken using a Knowledge-Based System (KBS) built upon the concepts and methods of human reasoning. Accordingly, a KBS was developed within the STREAMES project. In this KBS most of the knowledge needed for managing eutrophication problems was organised and structured in the form of a decision tree (DT). The methodology specially developed to build this KBS, as well as the internal structure of the eutrophication decision tree, is presented here. The good DT obtained led to consider the KBS a suitable tool to support the management of eutrophication.
Publisher version (URL): http://www.sciencedirect.com/science?_ob=ArticleURL&_udi=B6VBS-4WRCPH8-1&_user=4222402&_rdoc=1&_fmt=&_orig=search&_sort=d&_docanchor=&view=c&_searchStrId=1094961075&_rerunOrigin=google&_acct=C000048559&_version=1&_urlVersion=0&_userid=4222402&md5=7f3a558ae4bc5129b7a018aadf873cad
URI: http://hdl.handle.net/10261/18689
DOI: 10.1016/j.ecolmodel.2009.06.012
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