改进型模糊神经网络模型的构造  

Construction of Improved Fuzzy Neural Network Model

作　　者：刘云辉[1] 李钟慎[1] 

机构地区：[1]华侨大学机电及自动化学院,福建泉州362021

出　　处：《华侨大学学报（自然科学版）》2010年第3期256-259,共4页Journal of Huaqiao University(Natural Science)

基　　金：福建省自然科学基金资助项目(E0710018)

摘　　要：利用模糊系统和神经网络的优势,构造一种改进型模糊神经网络模型.从极大-极小模糊算子的模糊神经元入手,提出改进的修改模糊权值的训练学习规则.改进后的模糊神经网络模型大大减少了运算量,提高了收敛速度.采用此学习算法对实际汽轮发电机组运行状态进行监测,结果表明,模型具有较强的状态监测能力,达到预期的目的.The advantages of fuzzy system and neural network are taken to establish a kind of improved fuzzy neural network（FNN） models.An improved learning algorithm with the modified fuzzy weight is proposed on the basis of the fuzzy neurons model for the max-min fuzzy operator.The amount of calculation for the improved FNN model is reduced greatly and the convergence velocity is improved.The state monitoring of the practical turbo generator unit is run using the learning algorithm,and the results have indicated that the model has greater capability of state monitoring and the expected goal is obtained.

关 键 词：模糊神经网络模型 模糊神经元 学习规则 状态监测 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程]