李希勇, 张义良. 基于模糊神经网络的故障检测算法[J]. 微电子学与计算机, 2015, 32(9): 49-53. DOI: 10.19304/j.cnki.issn1000-7180.2015.09.010
引用本文: 李希勇, 张义良. 基于模糊神经网络的故障检测算法[J]. 微电子学与计算机, 2015, 32(9): 49-53. DOI: 10.19304/j.cnki.issn1000-7180.2015.09.010
LI Xi-yong, ZHANG Yi-liang. The Failure Detection Algorithm Based on Fuzzy Neural Network[J]. Microelectronics & Computer, 2015, 32(9): 49-53. DOI: 10.19304/j.cnki.issn1000-7180.2015.09.010
Citation: LI Xi-yong, ZHANG Yi-liang. The Failure Detection Algorithm Based on Fuzzy Neural Network[J]. Microelectronics & Computer, 2015, 32(9): 49-53. DOI: 10.19304/j.cnki.issn1000-7180.2015.09.010

基于模糊神经网络的故障检测算法

The Failure Detection Algorithm Based on Fuzzy Neural Network

  • 摘要: 为了有效解决网络系统可能出现的故障,结合模糊神经网络提出了一种新的故障检测算法FDD-FNN(Failure Detection algorithm based on Fuzzy Neural Network).该算法根据特征信息熵建立了故障检测评价方法和最小偏差的优化模型,设计了模糊神经网络中输入层、模糊化层、模糊规则层和解模糊层,并且给出了具体的算法流程.通过建立网络仿真平台,深入分析了影响FDD-FNN算法的关键因素,同时对比研究了FDD-FNN算法与其他算法的性能情况,结果表明FDD-FNN算法具有较好的适应性.

     

    Abstract: In order to effectively detect the failure of network system, a novel detection algorithm FDMBFO (Failure Detection algorithm based on Fuzzy Neural Network) is proposed by fuzzy neural network. In this algorithm, the failure detection method and the minimum deviation optimization model have proposed by feature information entropy, and Input Layer, Fuzzy Layer, Fuzzy Rule Layer and Ambiguity Layer have designed. Then, the algorithm processes is presented. Finally, an experiment with simulation platform was conducted to study the key factors of FDD-FNN. Compared to performance of other algorithm, the results show that FDD-FNN has better adaptability.

     

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