Image Clustering Algorithm for Power Potential Sensitive Users Based on Genetic Optimization Neural Network
In order to solve the problem of low accuracy of power potential sensitive user portrait clustering and recognition re-sults,a power potential sensitive user portrait clustering algorithm based on genetic optimization neural network is proposed.Construct a portrait of power users and accurately depict the behavior of power users.The numerical,temporal,statistical and clustering features of power user portraits are selected as the input of convolutional neural network model to identify the poten-tially sensitive power user portraits.The improved genetic algorithm is used to optimize the convolution neural network to make the recognition result more accurate.The experimental results show that this method can cluster and identify the portraits of potentially sensitive power users,and the performance and accuracy of clustering and recognization are good.
genetic algorithmconvolutional neural networkuser portraitpotentially sensitive usersclustering algorithmdissimilarity function
万方数据
维普
