Earticle

초록

영어

Binary-tree support vector machine (SVM) has such advantages as small repeated operation workload, fast classification speed and dead zone inexistence, but the structural design can influence the classification accuracy thereof. In order to rationally design the structure of the binary-tress SVM, a multi-classification algorithm (AHP-BSVM) combining analytic hierarchy process (AHP) and binary-tree SVM is proposed in this paper. Firstly, the analytic hierarchy process is adopted to establish the evaluation system model so as to comprehensively evaluate multiple influencing factors for determining the weight values of various faults; then, the faults are ordered by the weight values and the structure of the binary-tree SVM is determined according to the fault sequence; finally, the proposed algorithm is adopted for fault diagnosis and analysis. The simulation experiment shows: compared with other algorithms, the proposed algorithm has higher recognition accuracy and higher classification accuracy, and is applicable to multi-classification, thus having good promotion prospect.

목차

Abstract
 1. Introduction
 2. Binary-tree Support Vector Machine
 3. Binary-tree Fused SVM
  3.1. Decision Preference
  3.2. AHP Fused Binary-Tree SVM
 4. Simulation Experiment
  4.1. Data Source
  4.2. Fault Feature Extraction
  4.3. Result and Analysis
 5. Conclusion
 Acknowledgement
 References

키워드

저자

• ZHANG Xing-yuan [ College of air-transport,ShangHai University Of Engineering Science, ShangHai 201620, China ]
• CHEN Minye [ College of air-transport,ShangHai University Of Engineering Science, ShangHai 201620, China ]
• XU Hai-rong [ College of air-transport,ShangHai University Of Engineering Science, ShangHai 201620, China ]
• LI Pei-qi [ College of air-transport,ShangHai University Of Engineering Science, ShangHai 201620, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605