Research on fuzzy modeling forecasting method based on stochastic neural network

Authors:
Li Bo;Zhang Shiying;Wang Xiufeng
Affiliations:
School of Management, Tianjin University, Tianjin 30072, China;School of Management, Tianjin University, Tianjin 30072, China;School of Information, Nankai University, 300071, China
Venue:
Systems Analysis Modelling Simulation
Year:
2003

Citing 4
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Abstract

In this article, a novel modeling forecasting method based on the combination of the Modified Takagi and Sugeno (MTS) fuzzy model and the stochastic neural network is presented. Expectation-Maximization (EM) algorithm is put forward to calculate the parameters of neural network structure and its weights. Theoretical analysis and prediction examples all show that the technique has strong universalized capabilities and the methods are effective.