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Incremental and Decremental Algorithms of Fuzzy Support Vector Regressor and Its Application

机译:模糊支持向量regressor的增量和递减算法及其应用

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A fuzzy support vector regressor (FSVR) modeling method and its incremental and decremental algorithms are proposed in this paper. Based on which, an on-line FSVR modeling method based on sliding time window is also proposed. Which uses the samples in the time window to build the dynamic system model, and with the slide of the time window, the proposed incremental and decremental algorithms are used to update the trained FSVR without from scratch. The proposed method is applied in predicting the yield of acrylonitrile, study results demonstrate the effectiveness of this method.
机译:本文提出了一种模糊支持向量回归(FSVR)建模方法及其增量和递增算法。基于此,还提出了一种基于滑动时间窗口的在线FSVR建模方法。它在时间窗口中使用样本来构建动态系统模型,并且使用时间窗口的幻灯片,所提出的增量和递减算法用于更新训练的FSVR,而不会从头开始更新训练的FSVR。所提出的方法应用于预测丙烯腈的产率,研究结果证明了该方法的有效性。

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