FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308115105> ?p ?o ?g. }

• W4308115105 abstract "Neural network modeling has become a special interest for many engineers and scientists to be utilized in different types of data as time series, regression, and classification and have been used to solve complicated practical problems in different areas, such as medicine, engineering, manufacturing, military, business. To utilize a prediction model that is based upon artificial neural network (ANN), some challenges should be addressed that optimal designing and training of ANN are major ones. ANN can be defined as an optimization task because it has many hyper parameters and weights that can be optimized. Metaheuristic algorithms such as swarm intelligence-based methods are a category of optimization methods that aim to find an optimal structure of ANN and to train the network by optimizing the weights. One of the commonly used swarm intelligence-based algorithms is particle swarm optimization (PSO) that can be used for optimizing ANN. In this study, we review the conducted research works on optimizing the ANNs using PSO. All studies are reviewed from two different perspectives: optimization of weights and optimization of structure and hyper parameters." @default.
• W4308115105 created "2022-11-08" @default.
• W4308115105 creator A5017611735 @default.
• W4308115105 creator A5069399610 @default.
• W4308115105 creator A5077727968 @default.
• W4308115105 date "2023-02-08" @default.
• W4308115105 modified "2023-10-18" @default.
• W4308115105 title "Designing Artificial Neural Network Using Particle Swarm Optimization: A Survey" @default.
• W4308115105 cites W141982089 @default.
• W4308115105 cites W1475705016 @default.
• W4308115105 cites W1498436455 @default.
• W4308115105 cites W1551711366 @default.
• W4308115105 cites W1888884532 @default.
• W4308115105 cites W1969487735 @default.
• W4308115105 cites W1999024143 @default.
• W4308115105 cites W2002536914 @default.
• W4308115105 cites W2006145851 @default.
• W4308115105 cites W2015304908 @default.
• W4308115105 cites W2020754962 @default.
• W4308115105 cites W2029440305 @default.
• W4308115105 cites W2029963932 @default.
• W4308115105 cites W2040266035 @default.
• W4308115105 cites W2041701367 @default.
• W4308115105 cites W2050729568 @default.
• W4308115105 cites W2051680981 @default.
• W4308115105 cites W2057367767 @default.
• W4308115105 cites W2059992053 @default.
• W4308115105 cites W2067878879 @default.
• W4308115105 cites W2083474188 @default.
• W4308115105 cites W2097333415 @default.
• W4308115105 cites W2104451122 @default.
• W4308115105 cites W2111305776 @default.
• W4308115105 cites W2116048577 @default.
• W4308115105 cites W2118840131 @default.
• W4308115105 cites W2141249818 @default.
• W4308115105 cites W2150355110 @default.
• W4308115105 cites W2155482699 @default.
• W4308115105 cites W2164531580 @default.
• W4308115105 cites W2165171393 @default.
• W4308115105 cites W2169272081 @default.
• W4308115105 cites W2292633882 @default.
• W4308115105 cites W2488644675 @default.
• W4308115105 cites W2522263958 @default.
• W4308115105 cites W2587345921 @default.
• W4308115105 cites W2609559763 @default.
• W4308115105 cites W2614573013 @default.
• W4308115105 cites W2736333670 @default.
• W4308115105 cites W2736980737 @default.
• W4308115105 cites W2766736793 @default.
• W4308115105 cites W2767363635 @default.
• W4308115105 cites W2908201512 @default.
• W4308115105 cites W2940391604 @default.
• W4308115105 cites W2954464033 @default.
• W4308115105 cites W2983586584 @default.
• W4308115105 cites W3151521170 @default.
• W4308115105 cites W4246598646 @default.
• W4308115105 cites W4248700461 @default.
• W4308115105 doi "https://doi.org/10.5772/intechopen.106139" @default.
• W4308115105 hasPublicationYear "2023" @default.
• W4308115105 type Work @default.
• W4308115105 citedByCount "0" @default.
• W4308115105 crossrefType "book-chapter" @default.
• W4308115105 hasAuthorship W4308115105A5017611735 @default.
• W4308115105 hasAuthorship W4308115105A5069399610 @default.
• W4308115105 hasAuthorship W4308115105A5077727968 @default.
• W4308115105 hasBestOaLocation W43081151051 @default.
• W4308115105 hasConcept C109718341 @default.
• W4308115105 hasConcept C119487961 @default.
• W4308115105 hasConcept C119857082 @default.
• W4308115105 hasConcept C122357587 @default.
• W4308115105 hasConcept C124101348 @default.
• W4308115105 hasConcept C126255220 @default.
• W4308115105 hasConcept C127413603 @default.
• W4308115105 hasConcept C154945302 @default.
• W4308115105 hasConcept C201995342 @default.
• W4308115105 hasConcept C2780451532 @default.
• W4308115105 hasConcept C33923547 @default.
• W4308115105 hasConcept C41008148 @default.
• W4308115105 hasConcept C50644808 @default.
• W4308115105 hasConcept C85617194 @default.
• W4308115105 hasConceptScore W4308115105C109718341 @default.
• W4308115105 hasConceptScore W4308115105C119487961 @default.
• W4308115105 hasConceptScore W4308115105C119857082 @default.
• W4308115105 hasConceptScore W4308115105C122357587 @default.
• W4308115105 hasConceptScore W4308115105C124101348 @default.
• W4308115105 hasConceptScore W4308115105C126255220 @default.
• W4308115105 hasConceptScore W4308115105C127413603 @default.
• W4308115105 hasConceptScore W4308115105C154945302 @default.
• W4308115105 hasConceptScore W4308115105C201995342 @default.
• W4308115105 hasConceptScore W4308115105C2780451532 @default.
• W4308115105 hasConceptScore W4308115105C33923547 @default.
• W4308115105 hasConceptScore W4308115105C41008148 @default.
• W4308115105 hasConceptScore W4308115105C50644808 @default.
• W4308115105 hasConceptScore W4308115105C85617194 @default.
• W4308115105 hasLocation W43081151051 @default.
• W4308115105 hasOpenAccess W4308115105 @default.
• W4308115105 hasPrimaryLocation W43081151051 @default.
• W4308115105 hasRelatedWork W1997830976 @default.
• W4308115105 hasRelatedWork W2070977815 @default.
• W4308115105 hasRelatedWork W2168185055 @default.

• next