神经网络集成在图书剔旧分类中的应用

在分析图书剔旧工作的基础上，指出用智能的方法解决图书剔旧问题的必要性。提出了可以用神经网络集成技术来解决该问题，并给出一种动态构建神经网络集成的方法，该方法在训练神经网络集成成员网络时不仅调整网络的连接权值，而且动态地构建神经网络集成中各成员神经网络的结构，从而在提高单个网络精度的同时，增加了各网络成员之间的差异度，减小了集成的泛化误差。实验证明该方法可以有效地用于图书剔旧分类。

Application of Neural Network Ensembles in Book Weeding

Through analyzing the work of book weeding, it is known that to use the intelligent method in book weeding is very important. The neural network ensembles technology is a good idea for dealing with these problems. This paper presents a constructive method for training neural network ensembles. In training individual networks in ensembles, the proposed method not only adjusts the connection weights, but also makes the network architecture of the individual networks. So it improves the accuracy of the individual networks while increasing the diversity among the individual networks and decreasing the generalization error of network ensembles. Experiments prove that this ensemble is very effect in weeding books.