@inproceedings{355047a7cd3c404a9086a92f9523d395,
title = "Typhoon track prediction by a support vector machine using data reduction methods",
abstract = "Typhoon track prediction has mostly been achieved using numerical models which include a high degree of nonlinearity in the computer program. These numerical methods are not perfect and sometimes the forecasted tracks are far from those observed. Many statistical approaches have been utilized to compensate for these shortcomings in numerical modeling. In the present study, a support vector machine, which is well known to be a powerful artificial intelligent algorithm highly available for modeling nonlinear systems, is applied to predict typhoon tracks. In addition, a couple of input dimension reduction methods are also used to enhance the accuracy of the prediction system by eliminating irrelevant features from the input and to improve computational performance.",
author = "Song, {Hee Jun} and Huh, {Sung Hoe} and Kim, {Joo Hong} and Ho, {Chang Hoi} and Park, {Seon Ki}",
year = "2005",
doi = "10.1007/11596448_74",
language = "English",
isbn = "3540308180",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "503--511",
booktitle = "Computational Intelligence and Security - International Conference, CIS 2005, Proceedings",
note = "International Conference on Computational Intelligence and Security, CIS 2005 ; Conference date: 15-12-2005 Through 19-12-2005",
}