Improved Brain Emotional Learning Algorithm for Fast Classification

被引：0
|
作者：
Mei Y. [1 ,2 ]
Tan G.-Z. [1 ]
Liu Z.-T. [3 ]
机构：
[1] School of Information Science and Engineering, Central South University, Changsha, 410083, Hunan
[2] School of Electrical and Information Engineering, Hunan University of Arts and Science, Changde, 415000, Hunan
[3] School of Automation, China University of Geoscience, Wuhan, 430074, Hubei
来源：
Tien Tzu Hsueh Pao/Acta Electronica Sinica | 2017年 / 45卷 / 11期
关键词：
Brain emotional learning; Datasets; Fast classification; Genetic algorithm;
D O I：
10.3969/j.issn.0372-2112.2017.11.013
中图分类号：
学科分类号：
摘要：
An improved fast classification algorithm based on Brain Emotional Learning (BEL) and Genetic Algorithm (GA) is proposed to enhance the accuracy and efficiency.Inspired by the neurobiology research of emotional learning mechanism in amygdala and orbitofrontal cortex, the BEL model is constructed to mimic the mechanism of emotional stimulus processing in human brain.For the short path in the emotional brain, BEL can speed up the learning process.Furthermore, the learning weights in BEL are optimized by GA in order to improve the accuracy.Experiments using UCI datasets are performed, by which the results show that GA-BEL classification obtains higher accuracy and less computing time compared to other classifiers, in both small and large sample datasets. © 2017, Chinese Institute of Electronics. All right reserved.
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收藏
页码：2663 / 2670
页数：7
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