Application of support vector machines to accelerate the solution speed of metaheuristic algorithms

Shiyou Yang, Qing H. Liu, Junwei Lu, Siu Lau Ho, Guangzheng Ni, Peihong Ni, Suming Xiong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

7 Citations (Scopus)


The support vector machine (SVM) is proposed as a response surface model to accelerate the solution speed of metaheuristic algorithms in solving inverse problems. The detail formulations of the SVM regression model using $\varepsilon$-insensitive loss function are derived. Primary numerical results are reported to demonstrate the feasibility, performance, and robustness of the proposed SVM based response surface model for solving both mathematical functions and engineering design problems.
Original languageEnglish
Article number4787455
Pages (from-to)1502-1505
Number of pages4
JournalIEEE Transactions on Magnetics
Issue number3
Publication statusPublished - 1 Mar 2009


  • Inverse problem
  • Metaheuristic algorithm
  • Response surface model
  • Support vector machine (SVM)

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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