关键词: 神经网络, 量子免疫克隆算法, 目标分类, 冗余连接, 网络优化

Abstract: In order to reduce the redundant connections and unnecessary computing cost, quantum-inspired clonal algorithm was applied to optimize neural networks. By generating neural network weights which have certain sparse ratio, the algorithm not only effectively removed redundant neural network connections and hidden layer nodes, but also improved the learning efficiency of neural network, the approximation of function accuracy and generalization ability. This method had been applied to wild relics security system of Emperor Qinshihuang's mausoleum site museum, and the results show that the method can raise the probability of target classification and reduce the false alarm rate.

Key words: neural network, quantum-inspired clonal algorithm, target classification, redundant connection, network optimization