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Fuzzy least squares support vector machine soft measurement model based on adaptive mutative scale chaos immune algorithm

机译:基于自适应变尺度混沌免疫算法的模糊最小二乘支持向量机软测量模型。

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摘要

In order to enhance measuring precision of the real complex electromechanical system,complex industrial system and complex ecological & management system with characteristics of multi-variable,non-liner,strong coupling and large time-delay,in terms of the fuzzy character of this real complex system,a fuzzy least squares support vector machine(FLS-SVM) soft measurement model was established and its parameters were optimized by using adaptive mutative scale chaos immune algorithm.The simulation results reveal that fuzzy least squares support vector machines soft measurement model is of better approximation accuracy and robustness.And application results show that the relative errors of the soft measurement model are less than 3.34%.

著录项

  • 来源
    《中南大学学报(英文版)》 |2014年第2期|593-599|共7页
  • 作者

    WANG Tao-sheng; ZUO Hong-yan;

  • 作者单位

    Research Center of Engineering Technology for Engineering Vehicle Chassis Manufacturing of Hunan Province, Changsha 410205, China;

    Research Base of Multinational Investment and Operations in Hunan Province, Changsha 410205, China;

    Research Center of Engineering Technology for Engineering Vehicle Chassis Manufacturing of Hunan Province, Changsha 410205, China;

    School of Resource and Safety Engineering, Central South University, Changsha 410083, China;

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  • 正文语种 eng
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  • 入库时间 2022-08-18 01:07:05
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