| 基于模糊神经网络的粗糙集在股市预测中的应用 |
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| 引用本文： | 叶德谦 马志强 李帼 姜皇普. 基于模糊神经网络的粗糙集在股市预测中的应用[J]. 计算机科学, 2008, 35(4): 168-169 |
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| 作者姓名： | 叶德谦 马志强 李帼 姜皇普 |
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| 作者单位： | 燕山大学中德信息技术合作研究所,秦皇岛,066004 |
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| 摘 要： | 提出在模糊神经网络中使用粗糙集理论进行网络的设计.在模糊神经网络中引入粗糙集理论,不仅可以去除模糊神经网络中输入层的冗余神经元而且可以确定隐含层神经元的数目,从而使模糊神经网络具有更准确的逼近收敛能力和较高的精度.最后应用于股票市场,在股票买卖时机预测中取得了良好的效果.
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| 关 键 词： | 粗糙集 模糊聚类 神经网络 股市预测 |
Rough Set Based on Fuzzy Neural Network for the Application in Prediction of Stock Market |
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| YE De-Qian,MA Zhi-Qiang,LI Guo,JIANG Huang-Pu (ICDZ - Institute for Information Technology,Yanshan University,Qinhuangdao. Rough Set Based on Fuzzy Neural Network for the Application in Prediction of Stock Market[J]. Computer Science, 2008, 35(4): 168-169 |
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| Authors: | YE De-Qian MA Zhi-Qiang LI Guo JIANG Huang-Pu (ICDZ - Institute for Information Technology Yanshan University Qinhuangdao |
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| Abstract: | A new scheme of knowledge encoding in a fuzzy neural networks using rough set theoretical concepts is described. Introducing the rough theory in the fuzzy neural network can not only remove redundant neurons in the input layers of fuzzy neural, but also construct the neurons in the hidden layers. Thus enable the fuzzy neural network to have more accurate restraining ability and the high precision. Finally applies in the stock market, the stock business opportunity forecast has obtained the good effect. |
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| Keywords: | Rough sets theory Fuzzy clustering algorithm Neural network Prediction of stock market |
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