Time series prediction of earthquake input by using soft computing

被引:3
|
作者
Furuta, H [1 ]
Nomura, Y [1 ]
机构
[1] Kansai Univ, Dept Informat, Takatsuki, Osaka 5691095, Japan
来源
ISUMA 2003: FOURTH INTERNATIONAL SYMPOSIUM ON UNCERTAINTY MODELING AND ANALYSIS | 2003年
关键词
D O I
10.1109/ISUMA.2003.1236185
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Time series analysis is one of important issues in science, engineering, and so on. Up to the present statistical methods[1] such as AR model[2] and Kalman filter[3] have been successfully applied, however, those statistical methods may have problems for solving highly nonlinear problems. In this paper, an attempt is made to develop practical methods of nonlinear time series by introducing such Soft Computing techniques[4][5][6] as Chaos theory[7], Neural Network[8][9], GMDH[10][11] and fuzzy modeling[12][13]. Using the earthquake input record obtained in Hyogo, the applicability and accuracy of the proposed methods are discussed with a comparison of those results.
引用
收藏
页码:351 / 356
页数:6
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