Particle Swarm Optimization
Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a popul...
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| Μορφή: | Online |
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| Γλώσσα: | Αγγλικά |
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IntechOpen
2021
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| Διαθέσιμο Online: | ONIX_20210420_9789537619480_76 |
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| _version_ | 1869531058705268736 |
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| collection | Directory of Open Access Books |
| description | Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. |
| format | Online |
| id | doab-20.500.12854ir-64720 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| publisher | IntechOpen |
| publisherStr | IntechOpen |
| record_format | ojs |
| spelling | doab-20.500.12854ir-647202024-04-14T10:28:11Z Particle Swarm Optimization Lazinica, Aleksandar Computer architecture & logic design thema EDItEUR::U Computing and Information Technology::UY Computer science::UYF Computer architecture and logic design Particle swarm optimization (PSO) is a population based stochastic optimization technique influenced by the social behavior of bird flocking or fish schooling.PSO shares many similarities with evolutionary computation techniques such as Genetic Algorithms (GA). The system is initialized with a population of random solutions and searches for optima by updating generations. However, unlike GA, PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions, called particles, fly through the problem space by following the current optimum particles. This book represents the contributions of the top researchers in this field and will serve as a valuable tool for professionals in this interdisciplinary field. 2021-04-20T14:54:07Z 2021-04-20T14:54:07Z 2009 book ONIX_20210420_9789537619480_76 9789537619480 9789535157472 https://directory.doabooks.org/handle/20.500.12854/64720 eng image/jpeg n/a https://www.intechopen.com/books https://mts.intechopen.com/storage/books/3759/authors_book/authors_book.pdf IntechOpen IntechOpen 10.5772/109 10.5772/109 78a36484-2c0c-47cb-ad67-2b9f5cd4a8f6 9789537619480 9789535157472 IntechOpen 488 open access |
| spellingShingle | Computer architecture & logic design thema EDItEUR::U Computing and Information Technology::UY Computer science::UYF Computer architecture and logic design Particle Swarm Optimization |
| title | Particle Swarm Optimization |
| title_full | Particle Swarm Optimization |
| title_fullStr | Particle Swarm Optimization |
| title_full_unstemmed | Particle Swarm Optimization |
| title_short | Particle Swarm Optimization |
| title_sort | particle swarm optimization |
| topic | Computer architecture & logic design thema EDItEUR::U Computing and Information Technology::UY Computer science::UYF Computer architecture and logic design |
| topic_facet | Computer architecture & logic design thema EDItEUR::U Computing and Information Technology::UY Computer science::UYF Computer architecture and logic design |
| url | ONIX_20210420_9789537619480_76 |