| 自适应DNA免疫算法在化工软测量中的应用 |
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| 引用本文： | 许光泞,俞金寿.自适应DNA免疫算法在化工软测量中的应用[J].华东理工大学学报(自然科学版),2009,35(1). |
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| 作者姓名： | 许光泞 俞金寿 |
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| 作者单位： | 华东理工大学信息科学与工程学院,上海,200237 |
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| 摘 要： | 将T-S模糊模型与RBF神经网络相结合,构成T-S模糊RBF神经网络,提出了一种自适应DNA免疫算法优化设计T-S模糊RBF神经网络的规则后件参数的方法。该方法采用基于抗体浓度和克隆选择的更新策略调节机制,能有效地保持抗体的多样性,避免早熟收敛。将该方法应用于延迟焦化汽油干点的软测量建模,仿真结果表明了DNA免疫遗传算法在T-S模糊神经网络系统优化设计中的有效性,并可获得较高精度的模型。
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| 关 键 词： | RBF神经网络 DNA编码 自适应DNA免疫算法 T-S模糊模型 |
Application of Adaptive DNA Immune Algorithm in Chemical Soft-Sensing |
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| XU Guang-ning,YU Jin-shou.Application of Adaptive DNA Immune Algorithm in Chemical Soft-Sensing[J].Journal of East China University of Science and Technology,2009,35(1). |
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| Authors: | XU Guang-ning YU Jin-shou |
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| Institution: | School of Information Science and Engineering;East China University of Science and Technology;Shanghai 200237;China |
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| Abstract: | By combining T-S fuzzy model with RBF neural network,a new method for optimizing the coefficient of the consequence of T-S fuzzy RBF neural network is proposed via the adaptive DNA immune algorithm.In this method,the adjusting mechanism is based on antibody concentration and clone selection updating strategy so as to keep the antibody diversity and avoid the premature convergence.The proposed method is utilized to the soft-sensing modeling of the dry-point of gasoline delayed cooking.The experimental simula... |
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| Keywords: | RBF neural network DNA coding adaptive DNA immune algorithm T-S fuzzy model |
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