ABSTRACT
This paper mainly studies the application of artificial immune algorithms combined with principal component analysis in image processing. Firstly, the data set is preprocessed, and the main features are extracted by principal component analysis (PCA). And then we built a neural network. The parameters of the network structure are firstly optimized by using the artificial immune algorithm, and then the optimized parameters are substituted into the backpropagation neural network for training. The characteristics of the artificial immune algorithm can avoid BP neural network when optimizing network structural parameters into local optimal, and get a more reliable model.
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Index Terms
Image processing based on artificial immune algorithm
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