| 基于改进RBF神经网络的产业损害预警指数预报 |
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| 引用本文： | 郭恒川,任波.基于改进RBF神经网络的产业损害预警指数预报[J].铁路计算机应用,2011,20(11):4-7. |
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| 作者姓名： | 郭恒川 任波 |
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| 作者单位： | 洛阳理工学院 计算机与信息工程系,洛阳,471023 |
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| 基金项目： | 河南省产业损害预警系统研究(0513053700); 洛阳理工学院青年基金项目(2010QZ21) |
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| 摘 要： | 为了有效的保护产业安全,产业损害预警指数的预报成为重要的研究方向.针对这种非线性的时间序列和产业损害预警系统的应用特点,本文对RBF网络的学习算法进行了一定的改进,提高了预测结果的稳定性.根据实验仿真结果显示,该模型优于传统使用的分析方法,为各生产行业的生产计划提供决策支持.
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| 关 键 词： | RBF 神经网络 产业损害预警指数 仿真 |
| 收稿时间： | 2011-11-15 |
Forecast of Industry Injury Early-warning Index based on improved RBF Neural Networks |
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| GUO Heng-chuan
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REN Bo.Forecast of Industry Injury Early-warning Index based on improved RBF Neural Networks[J].Railway Computer Application,2011,20(11):4-7. |
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| Authors: | GUO Heng-chuan REN Bo |
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| Institution: | GUO Heng-chuan,REN Bo (Department of Computer and Information Engineering,Luoyang Institute of Science and Technology,Luoyang 471023,China) |
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| Abstract: | In order to protect industry security effectively,the forecast of Industry Injury Early-warning Index became an important research direction.In view of this nonlinear time series and the characteristics of Industry Injury Early-warning System,it was improved the algorithm of RBF Neural Networks,increased the stability of forecast.The simulation results of the experiment showed that the model was superior to the traditional methods,and could provide decision support for the production plant with various ente... |
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| Keywords: | RBF Neural Network Industry Injury Early-warning Index simulation |
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