基于抗体网络的邮件过滤器设计

抗体网络作为一种新型的基于免疫原理的神经网络模型,已有实验验证了其具有良好的无监督竞争学习能力。但对抗体网络的研究目前还集中在原理介绍和实验验证上,没有将其应用在实际工程问题中的先例。在保留抗体网络的结构自动生成,基于克隆选择、变异机制的无监督竞争学习等优点的同时,对抗体网络的初始化、抗体的表示方式、网络结构的更新等方面作了适当的改进。在此基础上设计的邮件过滤器,和传统的邮件过滤器相比,实验结果表明其具有自适应能力好、准确性高等优点。

A Design of Mail Filter Based on Antibody Network

The Antibody Network (ABNET), which is a new Artificial Neural Networks (ANN) based on immune principle, has been proved to have good ability of unsupervised and competitive learning in experiments. But there is no precedent to use ABNET in practical engineerings because the present researches about it are still focusing on principle and experiments. While the good qualities of ABNET are reserved, such as structure generated automatically, unsupervised and competitive learning based on clone selection and mutation,the way of initiating ABNET, expressing a antibody, and updating structure is improved properly. The mail filter based on improved ABNET is better at adaptation and accuracy in experiments, compared with traditional mail filters.