PSO method for r-SVR

doi:10.3778/j.issn.1002-8331.2009.29.012

Computer Engineering and Applications ›› 2009, Vol. 45 ›› Issue (29): 41-42.DOI: 10.3778/j.issn.1002-8331.2009.29.012

• 研究、探讨 • Previous Articles Next Articles

PSO method for r-SVR

FANG Yi-min¹，XU Bao-guo²

1.The School of Information Technology at Jiangnan University，Wuxi，Jiangsu 214063，China
2.The School of Communications and Control Engineering at Jiangnan University，Wuxi，Jiangsu 214063，China

Received:2008-05-28 Revised:2008-07-29 Online:2009-10-11 Published:2009-10-11
Contact: FANG Yi-min

r-SVR的PSO求解方法

方益民¹，徐保国²

1.江南大学信息学院，江苏无锡 214063
2.江南大学信控学院，江苏无锡 214063

通讯作者: 方益民

Abstract

Abstract: When r in r-SVR is less than 1，previous Newton descent method cannot be used for r-SVR.Hence，PSO algorithm is proposed to be used to solve r-SVR.In this paper，the fitness function is used in PSO for r-SVR and the relevant PSO algorithm is derived.Experimental results confirm that this method is effective.

Key words: support vector regression, r-loss function, particle swarm optimization

摘要： 针对r接近1时牛顿法不可求解r-SVR的问题，提出了r-SVR的PSO求解方法，推导出了PSO求解r-SVR的适应函数，给出了PSO求解r-SVR的算法和实验结果。结果表明，当r接近1时，牛顿法求解r-SVR失效，而PSO求解r-SVR的方法是有效的。

关键词: 支持向量回归机, r范数损失函数, 粒子群优化算法

CLC Number:

TP301

FANG Yi-min¹，XU Bao-guo². PSO method for r-SVR[J]. Computer Engineering and Applications, 2009, 45(29): 41-42.

方益民¹，徐保国². r-SVR的PSO求解方法[J]. 计算机工程与应用, 2009, 45(29): 41-42.

[1]	SHI Chuntian, ZENG Yanyang, HOU Shouming. Summary of Application of Swarm Intelligence Algorithms in Image Segmentation [J]. Computer Engineering and Applications, 2021, 57(8): 36-47.
[2]	MA Mengping, YANG Zhixia. Asymmetric [ν]-Kernel-Free Quadratic Surface Support Vector Regression [J]. Computer Engineering and Applications, 2021, 57(7): 70-77.
[3]	LI Jingxing, YANG Youlong. Feature Selection of Markov Blanket for High Dimensional Data [J]. Computer Engineering and Applications, 2021, 57(6): 58-66.
[4]	ZHU Jiaying, GAO Maoting. AUV Path Planning Based on Particle Swarm Optimization and Improved Ant Colony Optimization [J]. Computer Engineering and Applications, 2021, 57(6): 267-273.
[5]	HU Xiaomin, WANG Mingfeng, ZHANG Shourong, LI Min. New Differential Evolution with Particle Swarm Optimization Algorithm for Text Clustering [J]. Computer Engineering and Applications, 2021, 57(4): 61-67.
[6]	WANG Jiayue, SHI Li. Research on Path Optimization and Charging Strategy of Electric Refrigerated Vehicle Considering Cost of Battery Capacity Degradation [J]. Computer Engineering and Applications, 2021, 57(24): 283-289.
[7]	CHEN Wanfen, WANG Yujia, LIN Weixing. Heterogeneous Ensemble Surrogate Assisted Multi-objective Particle Swarm Optimization Algorithm [J]. Computer Engineering and Applications, 2021, 57(23): 71-80.
[8]	DU Shouxin, WU Tao. Study on Application of Double Population Hybrid Genetic Algorithm in Cut Order Planning [J]. Computer Engineering and Applications, 2021, 57(22): 182-189.
[9]	LIN Weixing, WANG Yujia, CHEN Wanfen, LIANG Haina. High-Dimensional Data Feature Selection Algorithm Based on Multifactor Particle Swarm Optimization [J]. Computer Engineering and Applications, 2021, 57(22): 199-207.
[10]	ZHANG Lin, WANG Tinghua, ZHOU Huiying. Research Progress on Parameter Optimization of SVR Based on Swarm Intelligence Algorithm [J]. Computer Engineering and Applications, 2021, 57(16): 50-64.
[11]	LI Leixiao, DENG Dan, LI Jie, WANG Yongsheng. All-to-All Comparison Computing Data Distribution Strategy Based on Particle Swarm Optimization [J]. Computer Engineering and Applications, 2021, 57(15): 109-117.
[12]	YU Guolong, ZHAO Yong, WU Lian, CUI Zhongwei. Improvement of QPSO Algorithm and Its Application in DBN Parameter Optimization [J]. Computer Engineering and Applications, 2021, 57(10): 154-162.
[13]	LIAO Weilin, CHENG Shan, SHANG Dongdong, WEI Zhaobin. Particle Swarm Optimization Algorithm Integrated with Multiple-Strategies [J]. Computer Engineering and Applications, 2021, 57(1): 69-76.
[14]	ZHOU Rong, LI Jun, WANG Hao. Reverse Learning Particle Swarm Optimization Based on Grey Wolf Optimization [J]. Computer Engineering and Applications, 2020, 56(7): 48-56.
[15]	HUO Lin, LU Yinli. Improved Particle Swarm Optimization for Android Malware Detection [J]. Computer Engineering and Applications, 2020, 56(7): 96-101.

PSO method for r-SVR

r-SVR的PSO求解方法

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics