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A new fuzzy comprehensive evaluation model based on the support vector machine

Author

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  • Si-dong Xian

    (Chongqing University of Posts and Telecommunications)

Abstract

In this paper, focused on a proper weight distribution vector of a fuzzy comprehensive evaluation method, a new fuzzy comprehensive evaluation model based on the supper vector machine (SVM) is proposed for overcoming the subjective limitation in traditional fuzzy comprehensive evaluation model. Furthermore, a multilevel fuzzy comprehensive evaluation model based on SVM of network learning has also been designed, and the improved algorithm is used to make an instant computation. This method gives good performance on determination of the weight distribution vector and improves the evaluation accuracy and generalization with an example.

Suggested Citation

  • Si-dong Xian, 2010. "A new fuzzy comprehensive evaluation model based on the support vector machine," Fuzzy Information and Engineering, Springer, vol. 2(1), pages 75-86, March.
    • Handle: RePEc:spr:fuzinf:v:2:y:2010:i:1:d:10.1007_s12543-010-0038-5
    DOI: 10.1007/s12543-010-0038-5
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    Cited by:

    1. Sidong Xian & Dong Qiu & Shiyun Zhang, 2013. "A Fuzzy Principal Component Analysis Approach to Hierarchical Evaluation Model for Balanced Supply Chain Scorecard Grading," Journal of Optimization Theory and Applications, Springer, vol. 159(2), pages 518-535, November.
    2. Yu Duan & Junnan Xiong & Weiming Cheng & Nan Wang & Yi Li & Yufeng He & Jun Liu & Wen He & Gang Yang, 2022. "Flood vulnerability assessment using the triangular fuzzy number-based analytic hierarchy process and support vector machine model for the Belt and Road region," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(1), pages 269-294, January.

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