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作者:

Wang, Yang (Wang, Yang.) | Chen, Yanyan (Chen, Yanyan.) (学者:陈艳艳)

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EI Scopus

摘要:

Predicting chaotic time series by fuzzy inference systems is one of active research areas. This paper concerns Mamdani and Sugeno fuzzy inference systems in the application of chaotic time series prediction. These two types of fuzzy inference systems were compared through four sets of experiments on a number of chaotic time series to evaluate their prediction performance in terms of model generalization, execution time, structure complexity, and noise tolerance. The experimental results indicate that it may as well choose Sugeno fuzzy inference system as a predictor in the first place for the situations where the training data are not severely corrupted by noise. © 2012 IEEE.

关键词:

Computer networks Forecasting Fuzzy inference Fuzzy systems Time series

作者机构:

  • [ 1 ] [Wang, Yang]Beijing Key Lab of Traffic Engineering, Beijing University of Technology, Beijing, China
  • [ 2 ] [Chen, Yanyan]Beijing Key Lab of Traffic Engineering, Beijing University of Technology, Beijing, China

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年份: 2012

页码: 438-442

语种: 英文

被引次数:

WoS核心集被引频次: 0

SCOPUS被引频次: 5

ESI高被引论文在榜: 0 展开所有

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