Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment
The conventional Particle Swarm Optimization (PSO) still has weaknesses in finding optimal solutions especially in a dynamic environment. Therefore, in this paper we proposed a Global best Local Neighborhood in particle swarm optimization in order to solve the optimum solution in dynamic environment...
| Main Authors: | , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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Faculty of Computer System & Software Engineering
2017
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/19973/1/Global%20best%20Local%20Neighbourhood%20in%20Particle%20Swarm.pdf |
| _version_ | 1825811876241473536 |
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| author | Zalili, Musa M. N. M., Kahar Mohd Hafiz, Mohd Hassin Rohani, Abu Bakar |
| author_facet | Zalili, Musa M. N. M., Kahar Mohd Hafiz, Mohd Hassin Rohani, Abu Bakar |
| author_sort | Zalili, Musa |
| collection | UMP |
| description | The conventional Particle Swarm Optimization (PSO) still has weaknesses in finding optimal solutions especially in a dynamic environment. Therefore, in this paper we proposed a Global best Local Neighborhood in particle swarm optimization in order to solve the optimum solution in dynamic environment. Based on the experimental results of 50 datasets, show that GbLN-PSO has the ability to find the quality solution in dynamic environment. |
| first_indexed | 2024-03-06T12:20:51Z |
| format | Conference or Workshop Item |
| id | UMPir19973 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:20:51Z |
| publishDate | 2017 |
| publisher | Faculty of Computer System & Software Engineering |
| record_format | dspace |
| spelling | UMPir199732018-07-27T02:03:30Z http://umpir.ump.edu.my/id/eprint/19973/ Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment Zalili, Musa M. N. M., Kahar Mohd Hafiz, Mohd Hassin Rohani, Abu Bakar QA76 Computer software The conventional Particle Swarm Optimization (PSO) still has weaknesses in finding optimal solutions especially in a dynamic environment. Therefore, in this paper we proposed a Global best Local Neighborhood in particle swarm optimization in order to solve the optimum solution in dynamic environment. Based on the experimental results of 50 datasets, show that GbLN-PSO has the ability to find the quality solution in dynamic environment. Faculty of Computer System & Software Engineering 2017-11 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/19973/1/Global%20best%20Local%20Neighbourhood%20in%20Particle%20Swarm.pdf Zalili, Musa and M. N. M., Kahar and Mohd Hafiz, Mohd Hassin and Rohani, Abu Bakar (2017) Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment. In: The 5th International Conference on Software Engineering & Computer System (ICSECS' 17) , 22-24 November 2017 , Adya Hotel, Pulau Langkawi, Malaysia. p. 76.. (Published) http://icsecs.ump.edu.my/index.php/en/program/program-book |
| spellingShingle | QA76 Computer software Zalili, Musa M. N. M., Kahar Mohd Hafiz, Mohd Hassin Rohani, Abu Bakar Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment |
| title | Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment |
| title_full | Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment |
| title_fullStr | Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment |
| title_full_unstemmed | Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment |
| title_short | Global best Local Neighbourhood in Particle Swarm Optimization for Big Data Environment |
| title_sort | global best local neighbourhood in particle swarm optimization for big data environment |
| topic | QA76 Computer software |
| url | http://umpir.ump.edu.my/id/eprint/19973/1/Global%20best%20Local%20Neighbourhood%20in%20Particle%20Swarm.pdf |
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