Soft Computing Approach for Time Series Prediction
| Authors: | Gao Yang, University of Surrey, United Kingdom
Joo Er Meng, Nanyang Technological University, Singapore |
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| Topic: | 3.2 Cognition and Control ( AI, Fuzzy, Neuro, Evolut.Comp.) |
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| Session: | Soft Computing for Control |
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| Keywords: | Time series analysis, Fuzzy logic, Neural networks, Autoregressive model |
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Abstract
This paper focuses on the modeling and prediction of nonlinear time series using a soft computing approach, namely fuzzy neural network (FNN). An efficient algorithm for model structure determination and parameter identification with the aim of producing improved predictive performance for noninear time series is developed. Experiments and comparative studies demonstrate that the proposed approaches can effectively learn complex temporal sequences in an adaptive way and they outperform some well-known fuzzy neural methods.
