Presentation 2001/6/22
Rainfall Forecast Using a Neural Network with a Real-Coded Genetical Preprocessing
Seiji Ito, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu,
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Abstract(in English) In this paper, rainfall is predicted by a Neural Network(NN) and a Genetic Algorithm(GA). GA selects data needed to predict the rainfall. NN learns and predicts it using attributes selected by GA. The real-coded GA is used to decide data priority, and data really needed for the rainfall forecast is selected based on the priority. Finally, in order to show the effectiveness of the proposed rainfall prediction system, computer simulations are performed for real weather data.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Neural Network / Real-Coded GA / Rainfall Forecast
Paper # NC2001-33
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Committee NC
Conference Date 2001/6/22(1days)
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Paper Information
Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Rainfall Forecast Using a Neural Network with a Real-Coded Genetical Preprocessing
Sub Title (in English)
Keyword(1) Neural Network
Keyword(2) Real-Coded GA
Keyword(3) Rainfall Forecast
1st Author's Name Seiji Ito
1st Author's Affiliation Department of Information Science & Intelligent Systems, Faculty of Engineering University of Tokushima()
2nd Author's Name Yasue Mitsukura
2nd Author's Affiliation Department of Information Science & Intelligent Systems, Faculty of Engineering University of Tokushima
3rd Author's Name Minoru Fukumi
3rd Author's Affiliation Department of Information Science & Intelligent Systems, Faculty of Engineering University of Tokushima
4th Author's Name Norio Akamatsu
4th Author's Affiliation Department of Information Science & Intelligent Systems, Faculty of Engineering University of Tokushima
Date 2001/6/22
Paper # NC2001-33
Volume (vol) vol.101
Number (no) 154
Page pp.pp.-
#Pages 5
Date of Issue