摘要
该文基于粗逻辑理论,研究了粗逻辑意义下的粗集神经网络的设计,分析和比较了粗逻辑神经网络和模糊逻辑神经网络的性质。在重庆地区Landsat TM遥感图像的地物分类实验中,验证了粗逻辑神经网络的有效性,同时可以发现其在网络结构和收敛性方面的优势。
In this paper, based on rough logic theory, the design of rough neural network in the meaning of rough logic is studied. The character of rough logic neural network and fuzzy logic neural network are analyzed and compared. The validity of the rough logic neural network can be verified in the land cover classification experiment of the Landsat TM remote sensing image of Chongqing area. The rough logic neural network has superiorities at the aspect of structure and convergence.
出处
《电子与信息学报》
EI
CSCD
北大核心
2007年第3期611-615,共5页
Journal of Electronics & Information Technology
基金
国家自然科学基金(60375001)
高等学校博士点基金(20030532004)
湖南省教育厅科研项目(05C093)资助课题
关键词
粗糙集
粗逻辑
粗逻辑神经网络
模糊逻辑神经网络
Rough set
Rough logic
Rough Logic Neural Network(RLNN)
Fuzzy Logic Neural Network(FLNN)