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A TWO-STAGE LEARNING METHOD TO CONFIGURE RBF CENTERS AND WIDTHS IN DYNAMIC ENVIRONMENT EMPLOYING IMMUNE OPERATIONS

机译：一种在采用免疫操作的动态环境中配置RBF中心和宽度的两级学习方法

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Xiaofeng Ling; Xinbao Gong; Xiaogang Zang; Ronghong Jin;
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年度 2011
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1. A TWO-STAGE LEARNING METHOD TO CONFIGURE RBF CENTERS AND WIDTHS IN DYNAMIC ENVIRONMENT EMPLOYING IMMUNE OPERATIONS [J] . Xiaofeng Ling, Xinbao Gong, Xiaogang Zang, Neural Network World . 2011,第4期

机译：在采用动态操作的动态环境中配置RBF中心和宽度的两阶段学习方法
2. Applicability of a Three-Stage Hybrid Model by Employing a Two-Stage Signal Decomposition Approach and a Deep Learning Methodology for Runoff Forecasting at Swat River Catchment, Pakistan [J] . Sibtain Muhammad, Li Xianshan, Azam Muhammad Imran, Polish Journal of Environmental Studies. . 2021,第1Pta1期

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4. Support vector machine classifiers using RBF kernels with clustering-based centers and widths [C] . Gao Daqi, Zhang Tao Neural Networks, The 2007 IEEE International Joint Conference on . 2007

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A TWO-STAGE LEARNING METHOD TO CONFIGURE RBF CENTERS AND WIDTHS IN DYNAMIC ENVIRONMENT EMPLOYING IMMUNE OPERATIONS

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