By Topic

An Improved Method on Meteorological Prediction Modeling using Genetic Algorithm and Artificial Neural Network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Long Jin ; Guangxi Research Institute of Meteorological Disasters Mitigation, Nanning 530022. E-mail: jinlong01@63.com ; Cai Yao ; Xiaoyan Huang

Aiming at forecasting typhoon tracks by using genetic algorithm and neural network approach, this paper presents a new prediction modeling scheme for selecting the structure of networks and determining the initial connection weight. The probability for obtaining a global optimal solution is raised by designing a strategy that the optimum individual for each generation is reserved after a certain number of generations in the computational process of genetic evolution. The case forecast results of the typhoon track over the South China sea area show that mean absolute error of the prediction during 1990-2003 is 150.0km form this new forecast model, and in comparison with the optimum individual form the last generation, under the conditions of the same predictors and period forecast error is 161.1km. Furthermore, it is also found that higher predictive accuracy form the forecast models using genetic algorithm and neural network approach, comparing the results to those form objective prediction technique of typhoon tracks and the climatology and persistence (CLIPER) methods

Published in:

2006 6th World Congress on Intelligent Control and Automation  (Volume:1 )

Date of Conference:

0-0 0