Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm
Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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2011
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| Online Access: | https://repo.uum.edu.my/id/eprint/13633/1/117.pdf |
| _version_ | 1803626637338607616 |
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| author | Hasan, Shafaatunnur Tan, Swee Quo Shamsuddin, Siti Mariyam Sallehuddin, Roselina |
| author_facet | Hasan, Shafaatunnur Tan, Swee Quo Shamsuddin, Siti Mariyam Sallehuddin, Roselina |
| author_sort | Hasan, Shafaatunnur |
| collection | UUM |
| description | Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in
enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning. |
| first_indexed | 2024-07-04T05:53:20Z |
| format | Conference or Workshop Item |
| id | uum-13633 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T05:53:20Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | uum-136332015-04-07T07:00:27Z https://repo.uum.edu.my/id/eprint/13633/ Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm Hasan, Shafaatunnur Tan, Swee Quo Shamsuddin, Siti Mariyam Sallehuddin, Roselina QA76 Computer software Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning. 2011 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/13633/1/117.pdf Hasan, Shafaatunnur and Tan, Swee Quo and Shamsuddin, Siti Mariyam and Sallehuddin, Roselina (2011) Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm. In: 3rd International Conference on Computing and Informatics (ICOCI 2011), 8-9 June 2011, Bandung, Indonesia. http://www.icoci.cms.net.my |
| spellingShingle | QA76 Computer software Hasan, Shafaatunnur Tan, Swee Quo Shamsuddin, Siti Mariyam Sallehuddin, Roselina Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm |
| title | Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm |
| title_full | Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm |
| title_fullStr | Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm |
| title_full_unstemmed | Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm |
| title_short | Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm |
| title_sort | artificial neural network learning enhancement using artificial fish swarm algorithm |
| topic | QA76 Computer software |
| url | https://repo.uum.edu.my/id/eprint/13633/1/117.pdf |
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