Journal of Advanced Computational Intelligence and Intelligent Informatics
Online ISSN : 1883-8014
Print ISSN : 1343-0130
ISSN-L : 1883-8014
Regular Papers
Weather Forecasting Using Artificial Neural Network and Bayesian Network
Klent Gomez AbistadoCatherine N. ArellanoElmer A. Maravillas
著者情報
ジャーナル オープンアクセス

2014 年 18 巻 5 号 p. 812-817

詳細
抄録

This paper presents a scheme of weather forecasting using artificial neural network (ANN) and Bayesian network. The study focuses on the data representing central Cebu weather conditions. The parameters used in this study are as follows: mean dew point, minimum temperature, maximum temperature, mean temperature, mean relative humidity, rainfall, average wind speed, prevailing wind direction, and mean cloudiness. The weather data were collected from the PAG-ASA Mactan-Cebu Station located at latitude: 10°19’, longitude: 123°59’ starting from January 2011 to December 2011 and the values available represent daily averages. These data were used for training the multi-layered backpropagation ANN in predicting the weather conditions of the succeeding days. Some outputs from the ANN, such as the humidity, temperature, and amount of rainfall, are fed to the Bayesian network for statistical analysis to forecast the probability of rain. Experiments show that the system achieved 93%–100% accuracy in forecasting weather conditions.

著者関連情報

この記事は最新の被引用情報を取得できません。

© 2014 Fuji Technology Press Ltd.

This article is licensed under a Creative Commons [Attribution-NoDerivatives 4.0 International] license (https://creativecommons.org/licenses/by-nd/4.0/).
The journal is fully Open Access under Creative Commons licenses and all articles are free to access at JACIII Official Site.
https://www.fujipress.jp/jaciii/jc-about/
前の記事 次の記事
feedback
Top