Matches in SemOpenAlex for { <https://semopenalex.org/work/W1999024143> ?p ?o ?g. }
Showing items 1 to 82 of
82
with 100 items per page.
- W1999024143 abstract "Extreme Learning Machine (ELM) for Single-hidden Layer Feedforward Neural Network (SLFN) has been attracting attentions because of its faster learning speed and better generalization performance than those of the traditional gradient-based learning algorithms. However, it has been proven that generalization performance of ELM classifier depends critically on the number of hidden neurons and the random determination of the input weights and hidden biases. In this paper, we propose Variable-length Particle Swarm Optimization algorithm (VPSO) for ELM to automatically select the number of hidden neurons as well as corresponding input weights and hidden biases for maximizing ELM classifier's generalization performance. Experimental results have verified that the proposed VPSO-ELM scheme significantly improves the testing accuracy of classification problems." @default.
- W1999024143 created "2016-06-24" @default.
- W1999024143 creator A5010340252 @default.
- W1999024143 creator A5037208622 @default.
- W1999024143 creator A5061179511 @default.
- W1999024143 creator A5076465250 @default.
- W1999024143 date "2013-12-01" @default.
- W1999024143 modified "2023-09-26" @default.
- W1999024143 title "An improved extreme learning machine based on Variable-length Particle Swarm Optimization" @default.
- W1999024143 cites W141982089 @default.
- W1999024143 cites W1972812972 @default.
- W1999024143 cites W2015460328 @default.
- W1999024143 cites W2026471620 @default.
- W1999024143 cites W2028759731 @default.
- W1999024143 cites W2030184507 @default.
- W1999024143 cites W2040604977 @default.
- W1999024143 cites W2078622091 @default.
- W1999024143 cites W2096987757 @default.
- W1999024143 cites W2130378394 @default.
- W1999024143 cites W2138260443 @default.
- W1999024143 cites W2152195021 @default.
- W1999024143 cites W2154568261 @default.
- W1999024143 cites W2158054309 @default.
- W1999024143 cites W2159311532 @default.
- W1999024143 doi "https://doi.org/10.1109/robio.2013.6739599" @default.
- W1999024143 hasPublicationYear "2013" @default.
- W1999024143 type Work @default.
- W1999024143 sameAs 1999024143 @default.
- W1999024143 citedByCount "8" @default.
- W1999024143 countsByYear W19990241432014 @default.
- W1999024143 countsByYear W19990241432017 @default.
- W1999024143 countsByYear W19990241432018 @default.
- W1999024143 countsByYear W19990241432019 @default.
- W1999024143 countsByYear W19990241432020 @default.
- W1999024143 countsByYear W19990241432021 @default.
- W1999024143 countsByYear W19990241432023 @default.
- W1999024143 crossrefType "proceedings-article" @default.
- W1999024143 hasAuthorship W1999024143A5010340252 @default.
- W1999024143 hasAuthorship W1999024143A5037208622 @default.
- W1999024143 hasAuthorship W1999024143A5061179511 @default.
- W1999024143 hasAuthorship W1999024143A5076465250 @default.
- W1999024143 hasConcept C109718341 @default.
- W1999024143 hasConcept C11413529 @default.
- W1999024143 hasConcept C122357587 @default.
- W1999024143 hasConcept C126255220 @default.
- W1999024143 hasConcept C134306372 @default.
- W1999024143 hasConcept C154945302 @default.
- W1999024143 hasConcept C182365436 @default.
- W1999024143 hasConcept C2780150128 @default.
- W1999024143 hasConcept C33923547 @default.
- W1999024143 hasConcept C41008148 @default.
- W1999024143 hasConcept C50644808 @default.
- W1999024143 hasConcept C85617194 @default.
- W1999024143 hasConceptScore W1999024143C109718341 @default.
- W1999024143 hasConceptScore W1999024143C11413529 @default.
- W1999024143 hasConceptScore W1999024143C122357587 @default.
- W1999024143 hasConceptScore W1999024143C126255220 @default.
- W1999024143 hasConceptScore W1999024143C134306372 @default.
- W1999024143 hasConceptScore W1999024143C154945302 @default.
- W1999024143 hasConceptScore W1999024143C182365436 @default.
- W1999024143 hasConceptScore W1999024143C2780150128 @default.
- W1999024143 hasConceptScore W1999024143C33923547 @default.
- W1999024143 hasConceptScore W1999024143C41008148 @default.
- W1999024143 hasConceptScore W1999024143C50644808 @default.
- W1999024143 hasConceptScore W1999024143C85617194 @default.
- W1999024143 hasLocation W19990241431 @default.
- W1999024143 hasOpenAccess W1999024143 @default.
- W1999024143 hasPrimaryLocation W19990241431 @default.
- W1999024143 hasRelatedWork W1578420296 @default.
- W1999024143 hasRelatedWork W1997830976 @default.
- W1999024143 hasRelatedWork W2042536609 @default.
- W1999024143 hasRelatedWork W2134114282 @default.
- W1999024143 hasRelatedWork W2322270513 @default.
- W1999024143 hasRelatedWork W2372447950 @default.
- W1999024143 hasRelatedWork W2378509784 @default.
- W1999024143 hasRelatedWork W2558771234 @default.
- W1999024143 hasRelatedWork W3102725223 @default.
- W1999024143 hasRelatedWork W3201210475 @default.
- W1999024143 isParatext "false" @default.
- W1999024143 isRetracted "false" @default.
- W1999024143 magId "1999024143" @default.
- W1999024143 workType "article" @default.