Matches in SemOpenAlex for { <https://semopenalex.org/work/W2922284041> ?p ?o ?g. }
Showing items 1 to 87 of
87
with 100 items per page.
- W2922284041 abstract "Sewage treatment process has the following characteristics: nonlinear, delay etc, and is very complicated to establish the model for its control process. A reasonable model is set up for elaborate prediction effluent quality, which can satisfy the standard of the effluent water and requirements of energy saving simultaneously. Extreme learning machine (ELM), i.e the machine learning method that new lately developed has high accuracy, reliability and outstanding performance in prediction. To get higher prediction effect, in this paper, there are two ways are proposed to improve the ELM, (1) Optimizing the parameters. The ELM whose input weights and bias threshold are optimized by particle swarm optimization algorithm (PSO) and genetic algorithm (GA), respectively; (2) Changing learning mode. To develop an online sequential learning algorithm (OS) for the ELM with additive or radial basis function (RBF) hidden nodes in a unified framework. Therefore, the several comparison approaches refer to optimize the ELM, e.g., PSO-ELM, GA-ELM, OS-ELM are applied to effluent quality prediction, and chemical oxygen demand (COD) is taken as examples in this paper. The results show that PSO-ELM model has remarkably superior performance on effluent quality prediction than peer models in terms of mean absolute error, mean absolute percentage error, root mean square error, and coefficient of determination." @default.
- W2922284041 created "2019-03-22" @default.
- W2922284041 creator A5010243176 @default.
- W2922284041 creator A5072070511 @default.
- W2922284041 date "2018-08-01" @default.
- W2922284041 modified "2023-10-10" @default.
- W2922284041 title "Comparative Study of Optimization Intelligent Models in Wastewater Quality Prediction" @default.
- W2922284041 cites W1132038451 @default.
- W2922284041 cites W1968442252 @default.
- W2922284041 cites W1979919415 @default.
- W2922284041 cites W1985376801 @default.
- W2922284041 cites W1995917979 @default.
- W2922284041 cites W2014242872 @default.
- W2922284041 cites W2065584454 @default.
- W2922284041 cites W2097612618 @default.
- W2922284041 cites W2111072639 @default.
- W2922284041 cites W2117953457 @default.
- W2922284041 cites W2158054309 @default.
- W2922284041 cites W2321045787 @default.
- W2922284041 cites W2605495425 @default.
- W2922284041 cites W2743826023 @default.
- W2922284041 cites W2792071392 @default.
- W2922284041 cites W3141671261 @default.
- W2922284041 doi "https://doi.org/10.1109/sdpc.2018.8664791" @default.
- W2922284041 hasPublicationYear "2018" @default.
- W2922284041 type Work @default.
- W2922284041 sameAs 2922284041 @default.
- W2922284041 citedByCount "4" @default.
- W2922284041 countsByYear W29222840412020 @default.
- W2922284041 countsByYear W29222840412021 @default.
- W2922284041 countsByYear W29222840412022 @default.
- W2922284041 crossrefType "proceedings-article" @default.
- W2922284041 hasAuthorship W2922284041A5010243176 @default.
- W2922284041 hasAuthorship W2922284041A5072070511 @default.
- W2922284041 hasConcept C105795698 @default.
- W2922284041 hasConcept C11413529 @default.
- W2922284041 hasConcept C119857082 @default.
- W2922284041 hasConcept C121332964 @default.
- W2922284041 hasConcept C126255220 @default.
- W2922284041 hasConcept C139945424 @default.
- W2922284041 hasConcept C150217764 @default.
- W2922284041 hasConcept C154945302 @default.
- W2922284041 hasConcept C163258240 @default.
- W2922284041 hasConcept C167085575 @default.
- W2922284041 hasConcept C2780150128 @default.
- W2922284041 hasConcept C33923547 @default.
- W2922284041 hasConcept C41008148 @default.
- W2922284041 hasConcept C43214815 @default.
- W2922284041 hasConcept C50644808 @default.
- W2922284041 hasConcept C62520636 @default.
- W2922284041 hasConcept C85617194 @default.
- W2922284041 hasConcept C8880873 @default.
- W2922284041 hasConceptScore W2922284041C105795698 @default.
- W2922284041 hasConceptScore W2922284041C11413529 @default.
- W2922284041 hasConceptScore W2922284041C119857082 @default.
- W2922284041 hasConceptScore W2922284041C121332964 @default.
- W2922284041 hasConceptScore W2922284041C126255220 @default.
- W2922284041 hasConceptScore W2922284041C139945424 @default.
- W2922284041 hasConceptScore W2922284041C150217764 @default.
- W2922284041 hasConceptScore W2922284041C154945302 @default.
- W2922284041 hasConceptScore W2922284041C163258240 @default.
- W2922284041 hasConceptScore W2922284041C167085575 @default.
- W2922284041 hasConceptScore W2922284041C2780150128 @default.
- W2922284041 hasConceptScore W2922284041C33923547 @default.
- W2922284041 hasConceptScore W2922284041C41008148 @default.
- W2922284041 hasConceptScore W2922284041C43214815 @default.
- W2922284041 hasConceptScore W2922284041C50644808 @default.
- W2922284041 hasConceptScore W2922284041C62520636 @default.
- W2922284041 hasConceptScore W2922284041C85617194 @default.
- W2922284041 hasConceptScore W2922284041C8880873 @default.
- W2922284041 hasLocation W29222840411 @default.
- W2922284041 hasOpenAccess W2922284041 @default.
- W2922284041 hasPrimaryLocation W29222840411 @default.
- W2922284041 hasRelatedWork W2070506065 @default.
- W2922284041 hasRelatedWork W2338648705 @default.
- W2922284041 hasRelatedWork W2781542012 @default.
- W2922284041 hasRelatedWork W2911598671 @default.
- W2922284041 hasRelatedWork W2922284041 @default.
- W2922284041 hasRelatedWork W2964938317 @default.
- W2922284041 hasRelatedWork W3174082714 @default.
- W2922284041 hasRelatedWork W3198703526 @default.
- W2922284041 hasRelatedWork W4214871907 @default.
- W2922284041 hasRelatedWork W4282934451 @default.
- W2922284041 isParatext "false" @default.
- W2922284041 isRetracted "false" @default.
- W2922284041 magId "2922284041" @default.
- W2922284041 workType "article" @default.