Particle Swarm Optimization in Regression Analysis:A Case Study

摘要：

　　In this paper, we utilized particle swarm optimization algo rithm to solve a regression analysis problem in dielectric relaxation field.The regression function is a nonlinear, constrained, and difficult prob lem which is solved by traditionally mathematical regression method.The regression process is formulated as a continuous, constrained, single objective problem, and each dimension is dependent in solution space.The object of optimization is to obtain the minimum sum of abso lute difference values between observed data points and calculated data points by the regression function.Experimental results show that particle swarm optimization can obtain good performance on regression analysis problems.

关键词： Particle swarm optimization regression analysis regression models weighted least absolute difference value

作者: Shi Cheng Chun Zhao Jingjin Wu Yuhui Shi

作者单位: Department of Electrical Engineering and Electronics,University of Liverpool, Liverpool, UK ;Departm Department of Electrical & Electronic Engineering,Xian Jiaotong-Liverpool University, Suzhou, China

会议类型: 国际会议

会议名称: 4th international Conference,ICSI2013(第4届群体智能国际会议)

会议地点: 哈尔滨

会议语种:英文

页码: 55-63

在线出版日期: 2013-06-12（万方平台首次上网日期，不代表论文的发表时间）