| 基于粗糙径向基函数的瓦斯涌出量预测 |
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| 引用本文： | 付优.基于粗糙径向基函数的瓦斯涌出量预测[J].太原大学学报,2010,11(3):120-123. |
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| 作者姓名： | 付优 |
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| 作者单位： | [1]太原科技大学计算机科学与技术学院,山西太原030024 [2]山西建筑职业技术学院计算机工程系,山西太原030006 |
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| 摘 要： | 针对径向基网络对训练样本要求高的情形，将粗糙集和径向基神经网络相结合，提出粗糙径向基神经网络的方法，利用粗糙集对数据进行属性规约，得到适合径向基网络要求的数据，进而提高了其训练速度以及精度。将该方法应用在瓦斯涌出量预测的实验中，并将粗糙径向基神经网络和BP网络的预测结果进行对比，可以得出粗糙径向基网络预测效果比BP的效果好的结论，同时证实该方法的可行性。
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| 关 键 词： | 粗糙集 径向基神经网络 瓦斯涌出量 |
Forecasting Gas Emission Based on Rough Set RBF |
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| FU You.Forecasting Gas Emission Based on Rough Set RBF[J].Journal of Taiyuan University,2010,11(3):120-123. |
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| Authors: | FU You |
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| Institution: | FU You (1. Computer Science and Technology Institute, Taiyuan University of Science and Technology, Taiyuan, 030024, China; 2. Computer Engineering Department, Shanxi Architectural Technology Institute, Taiyuan, 030006, China) |
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| Abstract: | As RNF has high requirements on the training samples, we can combine rough set with RNF and get a method of rough set RNF. By stipulating the data with rough set, we can get the data which can meet the requirements of RNF. Thus the training speed and accuracy can be increased. We apply this method in the forecasting experiment of gas emission, and compare the prediction result of rough set RNF with that of BP net, we can conclude that the prediction result of rough set RNF is better than that of BP. At the same time we confirm that this method is feasible. |
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| Keywords: | rough set RBF gas emission |
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