Design of genetic fog occurrence forecasting system by using LVQ network

Y. Mitsukura, M. Fukumi, N. Akamatsu

研究成果: Conference article

抜粋

A transportation development in recent years is quite remarkable. However, poor visibility often cause an accident. Therefore, it is very important to forecast a fog occurrence. In this paper, we propose a scheme to forecast a fog occurrence by using the Learning Vector Quantization (LVQ) and a Genetic Algorithm (GA). This scheme forecasts the fog occurrence by the weather data which are provided from the Japan Meteorological Agency. First, the provided data formation are shown. Next, the prediction scheme is described in detail. In this method, input attributes for a LVQ network are selected by real-coded GA to improve forecast accuracy. Furthermore, a partial selection processing in the real-coded GA improves its convergence properties. Finally, in order to show the effectiveness of the proposed prediction scheme, computer simulations are performed.

元の言語English
ページ(範囲)3678-3681
ページ数4
ジャーナルProceedings of the IEEE International Conference on Systems, Man and Cybernetics
5
出版物ステータスPublished - 2000 12 1
外部発表Yes
イベント2000 IEEE International Conference on Systems, Man and Cybernetics - Nashville, TN, USA
継続期間: 2000 10 82000 10 11

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Hardware and Architecture

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