Ant Colony Optimization for the Design of Modular Neural Networks in Pattern Recognition

被引：0
|
作者：
Valdez, Fevrier [1 ]
Castillo, Oscar [1 ]
Melin, Patricia [1 ]
机构：
[1] Tijuana Inst Technol, Tijuana Bc, Mexico
来源：
2016 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2016年
关键词：
Ant Colony Optimization; Neural Networks; Recognition; SYSTEM;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We describe in this paper the architecture of a modular neural network (MNN) for pattern recognition. More recently, the study of modular neural network techniques theory has been receiving significant attention. The design of a recognition system also requires careful attention. The paper aims to use the Ant Colony paradigm to optimize the architecture of this Modular Neural Network for pattern recognition in order to obtain a good percentage of image identification and in the shortest time possible.
引用
收藏
页码：163 / 168
页数：6
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