BP neural network is introduced to the fault location field of DWDM optical network in this paper. The alarm characteris-tics of the optical network equipments are discussed,and alarm vector and fault vector diagrams are generated by analyzing some typical instances. A 17×14×18 BP neural network structure is constructed and trained by using MATLAB. By comparing the training performances,the best training algorithm of fault location among the three training algorithms is chosen. Numerical simulation results indicate that the sum squared error (SSE) of fault location is less than 0.01,and the processing time is less than 100 ms. This method not only well deals with the missing alarms or false alarms,but also improves the fault location accuracy and real-time ability.
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机译:Discussion of 'Maximum Gradient Decision-Making for Railways Based on Convolutional Neural Network' by Hao Pu, Hong Zhang, Paul Schonfeld, Wei Li, Jie Wang, Xianbao Peng, and Jianping Hu
机译:基于优化遗传神经网络的井下运输机械滚动轴承故障诊断(The Application of Optimizing the GENETIC NEURAL NETWORK to the Fault Diagnosis of Rolling Bearings of Transporting Machinery Underground)