| 基于粗糙集与RBF神经网络的农业总产值预测方法 |
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| 引用本文： | 杜智慧,俞晓红.基于粗糙集与RBF神经网络的农业总产值预测方法[J].洛阳工业高等专科学校学报,2010,20(1). |
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| 作者姓名： | 杜智慧 俞晓红 |
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| 作者单位： | 1. 洛阳师范学院数学科学学院,河南,洛阳,471000
2. 洛阳理工学院数理部,河南,洛阳,471023 |
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| 摘 要： | 提出了把粗糙集和R BF神经网络相结合应用于农业总产值预测的方法。首先用粗糙集对影响农业总产值的多个因素进行属性约简,选择主要影响因素,去除冗余信息;然后利用RBF神经网络建立预测模型。最后对该模型的预测结果与因子分析神经网络模型的预测结果进行了比较,表明了该模型的有效性和优越性。
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| 关 键 词： | 粗糙集 属性约简 RBF神经网络 |
Forecasting Method for Farming Gross Output Based on Rough Set and RBF Neural Network |
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| DU Zhi-Hui,YU Xiao-Hong.Forecasting Method for Farming Gross Output Based on Rough Set and RBF Neural Network[J].Journal of Luoyang Technology College,2010,20(1). |
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| Authors: | DU Zhi-Hui YU Xiao-Hong |
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| Institution: | 1.Luoyang Normal University/a>;Luoyang 471000/a>;China/a>;2.Department of mathematics and physics/a>;Luoyang Institute of Science and Technology/a>;Luoyang 471023/a>;China |
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| Abstract: | A new method for forecasting the farming gross output with rough set and RBF neural network has been presented in this paper.Firstly the main influencing factors are chosen based on attributes reduction of rough sets,and the redundancy factors are removed.Then a forecasting model is founded by using RBF neural network.Finally comparisons are made between the forecasting results of the new model and the factor analysis neural network,to prove the efficiency and advantages of the new one. |
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| Keywords: | rough set attribute reduction RBF neural network |
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