dc.contributorUniversidade Estadual Paulista (Unesp)
dc.date.accessioned2014-05-27T11:24:50Z
dc.date.accessioned2022-10-05T18:23:14Z
dc.date.available2014-05-27T11:24:50Z
dc.date.available2022-10-05T18:23:14Z
dc.date.created2014-05-27T11:24:50Z
dc.date.issued2010-11-25
dc.identifier2010 IEEE World Congress on Computational Intelligence, WCCI 2010.
dc.identifierhttp://hdl.handle.net/11449/71968
dc.identifier10.1109/FUZZY.2010.5584172
dc.identifierWOS:000287453602073
dc.identifier2-s2.0-78549261727
dc.identifier6249842109354856
dc.identifier0000-0002-2042-018X
dc.identifier0000-0003-3390-8747
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/3921078
dc.description.abstractDue to growing urbanization and industrialization, the environment is suffering from pollution of rivers, degradation of soils and deteriorated air quality. Quality indices appear to be useful to evaluate the conditions of these media. The aim of this study was the development of a water quality index using a fuzzy inference system, since such an approach has proved advantageous in addressing problems that are subjective by nature or for which the data are uncertain. The methodology employed was based on this inference system, and considered the nine water quality parameters employed by CETESB (Companhia de Tecnologia de Saneamento Ambiental, São Paulo, Brazil) to evaluate water quality. After assessment of the data using the index, a comparison was made with the WQI (Water Quality Index), which is used for the monitoring of various water bodies, including in the study region. The results obtained using the index developed on the basis of fuzzy inference were found to be more useful than those derived from the method currently used by CETESB, since losses and/or omissions concerning individual parameters were minimized. © 2010 IEEE.
dc.languageeng
dc.relation2010 IEEE World Congress on Computational Intelligence, WCCI 2010
dc.rightsAcesso aberto
dc.sourceScopus
dc.subjectFuzzy inference systems
dc.subjectInference systems
dc.subjectQuality indices
dc.subjectWater quality indexes
dc.subjectWater quality parameters
dc.subjectWaterbodies
dc.subjectAir quality
dc.subjectArtificial intelligence
dc.subjectFish
dc.subjectFuzzy inference
dc.subjectFuzzy systems
dc.subjectQuality assurance
dc.subjectQuality control
dc.subjectWater quality
dc.subjectRiver pollution
dc.titleDevelopment of a water quality index using a fuzzy logic: A case study for the sorocaba river
dc.typeTrabalho apresentado em evento


Este ítem pertenece a la siguiente institución