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RESEARCH ON FUZZY MODELING FORECASTING METHOD BASED ON STOCHASTIC NEURAL NETWORK

机译:基于随机神经网络的模糊建模预测方法研究

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摘要

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.
机译:本文提出了一种基于改进的高木和Sugeno(MTS)模糊模型与随机神经网络相结合的模型预测方法。提出了期望最大化算法来计算神经网络结构的参数及其权重。理论分析和预测实例均表明该技术具有较强的通用能力,是有效的。

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