标题:An Improved Extreme Learning Machine Based on Variable-length Particle Swarm Optimization
作者:Xue, Bingxia; Ma, Xin; Gu, Jason; Li, Yibin
通讯作者:Ma, X
作者机构:[Xue, Bingxia; Ma, Xin; Li, Yibin] Shandong Univ, Sch Control Sci & Engn, Jinan 250100, Shandong, Peoples R China.; [Gu, Jason] Dalhousie Univ, Dept 更多
会议名称:IEEE International Conference on Robotics and Biomimetics (ROBIO)
会议日期:DEC 12-14, 2013
来源:2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND BIOMIMETICS (ROBIO)
出版年:2013
页码:1030-1035
摘要:Extreme Learning Machine (ELM) for Single-hidden Layer Feedforward Neural Network (SLFN) has been attracting attentions because of its faster learning speed and better generalization performance than those of the traditional gradient-based learning algorithms. However, it has been proven that generalization performance of ELM classifier depends critically on the number of hidden neurons and the random determination of the input weights and hidden biases. In this paper, we propose Variable-length Particle Swarm Optimization algorithm (VPSO) for ELM to automatically select the number of hidden neurons as well as corresponding input weights and hidden biases for maximizing ELM classifier's generalization performance. Experimental results have verified that the proposed VPSO-ELM scheme significantly improves the testing accuracy of classification problems.
收录类别:CPCI-S
WOS核心被引频次:1
资源类型:会议论文
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