Comparison between fast EP-ANN and classical EP-ANN for lightning prediction: article / Azizi Ahmad Masduki
One of the methods for lightning prediction is by using an Artificial Neural Network (ANN) prediction system for lightning occurrence based on historical lightning and meteorological data from Malaysian Environment. Using this method has a few problems about to finding suitable network architectures...
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
Universiti Teknologi MARA (UiTM)
2011
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| オンライン･アクセス: | https://ir.uitm.edu.my/id/eprint/97467/1/97467.PDF https://ir.uitm.edu.my/id/eprint/97467/ |
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| 要約: | One of the methods for lightning prediction is by using an Artificial Neural Network (ANN) prediction system for lightning occurrence based on historical lightning and meteorological data from Malaysian Environment. Using this method has a few problems about to finding suitable network architectures. This paper presents the improvement of method ANN with Evolutionary Programming (EP) as an optimization technique. This optimization technique will optimize to find ANN architectures systematically with less computation time. The mutations operators in EP discuss in this paper are Fast EP which apply Cauchy mutation and classical-EP which apply Gaussian mutation and the comparison for both of its. The best value sets of input data taken whether by using a Cauchy or Gaussian mutations and both operators will be compare to decide which the most suitable operators for lightning prediction is. As the result, the most suitable technique will create the best ANN architectures. |
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