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An Improved Arithmetic Optimization Algorithm and Its Application to Determine the Parameters of Support Vector Machine

文献类型：期刊论文

作者Fang, Heping3,4; Fu, Xiaopeng2; Zeng, Zhiyong1; Zhong, Kunhua4; Liu, Shuguang4
刊名MATHEMATICS
出版日期2022-08-01
卷号10期号:16页码:20
关键词arithmetic optimization algorithm (AOA) dynamic inertia weights dynamic coefficient of mutation probability triangular mutation strategy support vector machine
DOI10.3390/math10162875
通讯作者Fang, Heping(fangheping@cigit.ac.cn) ; Liu, Shuguang(liushuguang@cigit.ac.cn)
英文摘要The arithmetic optimization algorithm (AOA) is a new metaheuristic algorithm inspired by arithmetic operators (addition, subtraction, multiplication, and division) to solve arithmetic problems. The algorithm is characterized by simple principles, fewer parameter settings, and easy implementation, and has been widely used in many fields. However, similar to other meta-heuristic algorithms, AOA suffers from shortcomings, such as slow convergence speed and an easy ability to fall into local optimum. To address the shortcomings of AOA, an improved arithmetic optimization algorithm (IAOA) is proposed. First, dynamic inertia weights are used to improve the algorithm's exploration and exploitation ability and speed up the algorithm's convergence speed; second, dynamic mutation probability coefficients and the triangular mutation strategy are introduced to improve the algorithm's ability to avoid local optimum. In order to verify the effectiveness and practicality of the algorithm in this paper, six benchmark test functions are selected for the optimization search test verification to verify the optimization search ability of IAOA; then, IAOA is used for the parameter optimization of support vector machines to verify the practical ability of IAOA. The experimental results show that IAOA has a strong global search capability, and the optimization-seeking capability is significantly improved, and it shows excellent performance in support vector machine parameter optimization.
资助项目Science and Technology Service Network Project of Chinese Academy of Sciences[KFJ-STS-QYZD-2021-01-001]
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000845481200001
出版者MDPI
源URL[http://119.78.100.138/handle/2HOD01W0/16530]  
专题中国科学院重庆绿色智能技术研究院
通讯作者Fang, Heping; Liu, Shuguang
作者单位1.Chongqing Univ Posts & Telecommun, Sch Comp Sci & Technol, Chongqing 400065, Peoples R China
2.Guangxi Minzu Univ, Sch Artificial Intelligence, Nanning 530006, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.Chinese Acad Sci, Chongqing Inst Green & Intelligent Technol, Chongqing 400714, Peoples R China
推荐引用方式
GB/T 7714		 Fang, Heping,Fu, Xiaopeng,Zeng, Zhiyong,et al. An Improved Arithmetic Optimization Algorithm and Its Application to Determine the Parameters of Support Vector Machine[J]. MATHEMATICS,2022,10(16):20.
APA Fang, Heping,Fu, Xiaopeng,Zeng, Zhiyong,Zhong, Kunhua,&Liu, Shuguang.(2022).An Improved Arithmetic Optimization Algorithm and Its Application to Determine the Parameters of Support Vector Machine.MATHEMATICS,10(16),20.
MLA Fang, Heping,et al."An Improved Arithmetic Optimization Algorithm and Its Application to Determine the Parameters of Support Vector Machine".MATHEMATICS 10.16(2022):20.

入库方式： OAI收割

来源：重庆绿色智能技术研究院

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