Matches in SemOpenAlex for { <https://semopenalex.org/work/W2091249059> ?p ?o ?g. }
Showing items 1 to 76 of
76
with 100 items per page.
- W2091249059 abstract "This paper deals with the study of a water quality prediction model through application of LS-SVM in Liuxi River in Guangzhou. To overcome the shortcomings of traditional BP algorithm as being slow to converge and easy to reach extreme minimum value, least squares support vector machine (LS-SVM) combined with particle swarm optimization (PSO) is used to time series prediction. The LS-SVM can overcome some shortcoming in the Multilayer Perceptron (MLP) and the PSO is used to tune the LS-SVM parameters automatically. It enhances the efficiency and the capability of prediction. Through simulation testing the model shows high efficiency in forecasting the water quality of the Liuxi River." @default.
- W2091249059 created "2016-06-24" @default.
- W2091249059 creator A5033669186 @default.
- W2091249059 creator A5060236348 @default.
- W2091249059 date "2009-01-01" @default.
- W2091249059 modified "2023-10-02" @default.
- W2091249059 title "Water Quality Prediction Using LS-SVM and Particle Swarm Optimization" @default.
- W2091249059 cites W1986490585 @default.
- W2091249059 cites W1988033067 @default.
- W2091249059 cites W2023632327 @default.
- W2091249059 cites W2072950067 @default.
- W2091249059 cites W2109364787 @default.
- W2091249059 cites W2142845953 @default.
- W2091249059 cites W2149306144 @default.
- W2091249059 cites W2150174329 @default.
- W2091249059 cites W2152195021 @default.
- W2091249059 cites W2165299997 @default.
- W2091249059 doi "https://doi.org/10.1109/wkdd.2009.217" @default.
- W2091249059 hasPublicationYear "2009" @default.
- W2091249059 type Work @default.
- W2091249059 sameAs 2091249059 @default.
- W2091249059 citedByCount "60" @default.
- W2091249059 countsByYear W20912490592012 @default.
- W2091249059 countsByYear W20912490592013 @default.
- W2091249059 countsByYear W20912490592014 @default.
- W2091249059 countsByYear W20912490592015 @default.
- W2091249059 countsByYear W20912490592016 @default.
- W2091249059 countsByYear W20912490592017 @default.
- W2091249059 countsByYear W20912490592018 @default.
- W2091249059 countsByYear W20912490592019 @default.
- W2091249059 countsByYear W20912490592020 @default.
- W2091249059 countsByYear W20912490592021 @default.
- W2091249059 countsByYear W20912490592022 @default.
- W2091249059 countsByYear W20912490592023 @default.
- W2091249059 crossrefType "proceedings-article" @default.
- W2091249059 hasAuthorship W2091249059A5033669186 @default.
- W2091249059 hasAuthorship W2091249059A5060236348 @default.
- W2091249059 hasConcept C119857082 @default.
- W2091249059 hasConcept C12267149 @default.
- W2091249059 hasConcept C124101348 @default.
- W2091249059 hasConcept C126255220 @default.
- W2091249059 hasConcept C145828037 @default.
- W2091249059 hasConcept C154945302 @default.
- W2091249059 hasConcept C179717631 @default.
- W2091249059 hasConcept C33923547 @default.
- W2091249059 hasConcept C41008148 @default.
- W2091249059 hasConcept C50644808 @default.
- W2091249059 hasConcept C85617194 @default.
- W2091249059 hasConceptScore W2091249059C119857082 @default.
- W2091249059 hasConceptScore W2091249059C12267149 @default.
- W2091249059 hasConceptScore W2091249059C124101348 @default.
- W2091249059 hasConceptScore W2091249059C126255220 @default.
- W2091249059 hasConceptScore W2091249059C145828037 @default.
- W2091249059 hasConceptScore W2091249059C154945302 @default.
- W2091249059 hasConceptScore W2091249059C179717631 @default.
- W2091249059 hasConceptScore W2091249059C33923547 @default.
- W2091249059 hasConceptScore W2091249059C41008148 @default.
- W2091249059 hasConceptScore W2091249059C50644808 @default.
- W2091249059 hasConceptScore W2091249059C85617194 @default.
- W2091249059 hasLocation W20912490591 @default.
- W2091249059 hasOpenAccess W2091249059 @default.
- W2091249059 hasPrimaryLocation W20912490591 @default.
- W2091249059 hasRelatedWork W1996541855 @default.
- W2091249059 hasRelatedWork W2091249059 @default.
- W2091249059 hasRelatedWork W2096504223 @default.
- W2091249059 hasRelatedWork W2111402576 @default.
- W2091249059 hasRelatedWork W2129327131 @default.
- W2091249059 hasRelatedWork W2374977502 @default.
- W2091249059 hasRelatedWork W251172239 @default.
- W2091249059 hasRelatedWork W3115048730 @default.
- W2091249059 hasRelatedWork W3195168932 @default.
- W2091249059 hasRelatedWork W4221021152 @default.
- W2091249059 isParatext "false" @default.
- W2091249059 isRetracted "false" @default.
- W2091249059 magId "2091249059" @default.
- W2091249059 workType "article" @default.