@inproceedings{84fa15e7bfb845deaadcbb93d35231aa,
title = "A chaotic time series prediction method based on fuzzy neural network and its application",
abstract = "An approach based on chaos theory and fuzzy neural network (FNN) is proposed for chaotic time series prediction. Firstly, C-C algorithm is applied to estimate the delay time of chaotic signal. Grassberger-Procaccia (G-P) algorithm and least squares regression are employed to calculate the correlation dimension of chaotic signal simultaneously. Considering the difficulty in determining the number of input nodes of FNN, minimum embedding dimension obtained from chaotic time series analysis is used to design FNN. It was proved from two study cases that the proposed model is efficient in the practical prediction of chaotic time series.",
keywords = "Chaos theory, Chaotic time series, Fuzzy neural network",
author = "Zhuo Chen and Chen Lu and Wenjin Zhang and Xiaowei Du",
year = "2010",
doi = "10.1109/IWCFTA.2010.106",
language = "英语",
isbn = "9780769542478",
series = "Proceedings - 2010 International Workshop on Chaos-Fractal Theories and Applications, IWCFTA 2010",
pages = "355--359",
booktitle = "Proceedings - 2010 International Workshop on Chaos-Fractal Theories and Applications, IWCFTA 2010",
note = "3rd International Workshop on Chaos-Fractals Theories and Applications, IWCFTA 2010 ; Conference date: 29-10-2010 Through 31-10-2010",
}