| 基于粗糙集理论的模糊神经网络及其在化纤生产过程中的应用 |
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| 引用本文： | 陈双叶,易继锴.基于粗糙集理论的模糊神经网络及其在化纤生产过程中的应用[J].中国工程科学,2001,3(12):42-46. |
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| 作者姓名： | 陈双叶 易继锴 |
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| 作者单位： | 北京工业大学,电子信息与控制工程学院,北京,100022 |
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| 基金项目： | "八六三"国家高技术计划资助项目（863-306-ZT01-07-1） |
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| 摘 要： | 提出一种基于粗糙集理论的模糊神经网络系统,首先运用粗糙集理论来发现大量样本数据中的概略化的规则,然后根据这些规则来设计神经网络的结构模型,并利用神经网络技术对模型进行训练。化纤工业中抽丝冷却侧吹风过程的模拟仿真实验,证明了该方法的有效性和可行性。
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| 关 键 词： | 粗糙集 模糊逻辑 神经网络 规则获取 |
| 收稿时间： | 6/1/2001 12:00:00 AM |
| 修稿时间： | 2001年6月1日 |
A Fuzzy Neural Network Based on Rough Sets and Its Applications to Chemical Fiber Production |
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| chenshuangye and yijixu.A Fuzzy Neural Network Based on Rough Sets and Its Applications to Chemical Fiber Production[J].Engineering Science,2001,3(12):42-46. |
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| Authors: | chenshuangye and yijixu |
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| Abstract: | A fuzzy neural network based on rough sets is presented in this paper. First, a set of rough rules are found from the given training data by using rough sets theory, then the structure and model are designed according these rules, and then the model is trained by neural network technique. The experiments that simulate the control process of side wind for chemical fiber are carried out. The results proved its efficiency and feasibility. |
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| Keywords: | rough sets fuzzy logic neural network rules extracted |
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