关键词: BP神经网络, 分类, 泛化能力, 人工蜂群

Abstract: Due to the issues of BP neural network, which is sensitive to initial weights and easy to make the objective function into local optimum, and the disadvantages of weak local search ability and poor exploitation in standard artificial bee colony algorithm, a training method of neural network called improved artificial bee colony and back propagation is proposed. First, modify artificial bee colony algorithm inspired by the thought of differential evolution and make a more accurate description of searching behavior of onlooker bees. Second, avoid BP neural network falling into local optimum, using improved artificial bee colony to globally search the initial weights of BP neural network. Last, the datasets are tested by the new algorithm. The experiment shows compared with traditional BP neural network, the algorithm has higher classification correctness and better generalization.

Key words: BP neural network, classification, generalization, artificial bee colony