Lévy mutation in artificial bee colony algorithm for gasoline price prediction
In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm. The purpose is to better exploit promising solutions found by the bees.Such an approach is used to improve the performance of the original ABC in optimizing Least Square...
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| 主要な著者: | , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English |
| 出版事項: |
2012
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| 主題: | |
| オンライン･アクセス: | http://repo.uum.edu.my/10963/1/CR180.pdf http://repo.uum.edu.my/10963/ http://www.kmice.uum.edu.my |
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| 要約: | In this paper, a mutation strategy that is based on Lévy Probabily Distribution is introduced in Artificial Bee Colony algorithm.
The purpose is to better exploit promising solutions found by the bees.Such an approach is used to improve the performance of the original ABC in optimizing Least Squares Support Vector Machine hyper parameters.From the conducted experiment, the proposed lvABC shows encouraging results in optimizing parameters of interest.The proposed.lvABC-LSSVM has outperformed existing prediction model, Backpropogation Neural Network (BPNN), in predicting gasoline price. |
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