作　　者： ; ; ;

机构地区： 湘潭大学

出　　处： 《控制与决策》 2005年第2期121-126,共6页

摘　　要： 通过对近10年发展起来的粗集神经网络集成技术的总结和归纳,可将粗集神经网络集成技术分为3种:粗集神经网络混合系统、粗边界神经网络和粗-颗粒神经网络.介绍了每种集成技术的研究现状,分析和阐述了其原理及特点.最后,总结了当前粗集神经网络集成技术中需关注的一些问题,并指出了进一步研究的方向. The rough neural network integration technology which has been developed for last decade is summarized and generalized. There are three main integration (techniques:) rough set and neural network hybrid system, rough boundary value neural network, and rough-granular neural network. The research status of each integration (technology) is introduced. The principle and characteristic of each integration technology are analyzed and (expounded.) At last, some problems need to be noticed in the technology are summed and directions for (further) (research) are presented.

关 键 词： 粗集 神经网络 信息颗粒 粗集神经网络

领　　域： [自动化与计算机技术] [自动化与计算机技术]