Neuro Rainfall Forecast with Data Mining by Real-Coded Genetical Preprocessing

Seiji Ito, Yasue Mitsukura, Minoru Fukumi, Norio Akamatsu

研究成果: Article査読

7 被引用数 (Scopus)

抄録

In this paper, rainfall is predicted by using 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 are selected based on the priority. In order to show the effectiveness of the proposed rainfall prediction system, computer simulations are performed for real weather data. Finally, the effectiveness of this system is shown with data analysis.

本文言語English
ページ(範囲)817-822
ページ数6
ジャーナルIEEJ Transactions on Electronics, Information and Systems
123
4
DOI
出版ステータスPublished - 2003 1月
外部発表はい

ASJC Scopus subject areas

  • 電子工学および電気工学

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