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Knowledge discovery with clustering based on rules by states: a water treatment application

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10.1016/j.envsoft.2009.11.004
 
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hdl:2117/8293

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Gibert, KarinaMés informacióMés informacióMés informació
Rodríguez Silva, Gustavo
Rodríguez Roda, Ignasi
Document typeArticle
Defense date2010-06
PublisherElsevier
Rights accessRestricted access - publisher's policy
Attribution-NonCommercial-NoDerivs 3.0 Spain
Except where otherwise noted, content on this work is licensed under a Creative Commons license : Attribution-NonCommercial-NoDerivs 3.0 Spain
Abstract
This work presents advances in the design of a hybrid methodology that combines artificial intelligence and statistical tools to induce a model of explicit knowledge in relation to the dynamics of a wastewater treatment plant. The methodology contributes to problem solving under the paradigm of knowledge discovery from data in which the pre-process, the automatic interpretation of results and the explicit production of knowledge play a role as important as the analysis itself. The data mining step is performed using clustering based on rules by states, which integrates the knowledge discovered separately at each step of the process into a single model of global operation of the phenomenon. This provides a more accurate model for the dynamics of the system than one obtained by analyzing the whole dataset with all the steps taken together.
CitationGibert, C.; Rodríguez, G.; Rodríguez-Roda, I. Knowledge discovery with clustering based on rules by states: a water treatment application. "Environmental modelling and software", Juny 2010, vol. 25, núm. 6, p. 712-723. 
URIhttp://hdl.handle.net/2117/8293
DOI10.1016/j.envsoft.2009.11.004
ISSN1364-8152
Publisher versionhttp://www.sciencedirect.com/science?_ob=MImg&_imagekey=B6VHC-4Y0546T-1-H&_cdi=6063&_user=1517299&_pii=S136481520900293X&_orig=search&_coverDate=06%2F30%2F2010&_sk=999749993&view=c&wchp=dGLbVtb-zSkzk&md5=a9f79745f01e6ea03e7ee056201c83fb&ie=/sdarticle.pdf
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