| 棉叶螨发生趋势的RBF网络预报模型 |
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| 引用本文： | 刘婧然,马英杰,雷晓云,王喆.棉叶螨发生趋势的RBF网络预报模型[J].节水灌溉,2009(5). |
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| 作者姓名： | 刘婧然 马英杰 雷晓云 王喆 |
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| 作者单位： | 新疆农业大学水利与土木工程学院,乌鲁木齐,830052 |
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| 基金项目： | 国家高技术研究发展计划(“863”计划)资助项目(2006AA100218);;新疆自治区高技术研究与发展计划项目(200712111)。 |
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| 摘 要： | 采用RBF网络的方法,利用MATLAB工具箱并结合气象资料中的平均气温、最低气温、相对湿度和降雨量,建立了预报新疆石河子地区的棉叶螨发生程度的RBF神经网络预报系统.该系统通过实例证实了预报的准确性,并且与常用的BP网络进行了比较.通过程序记时显示RBF网络训练用时0.079 s,比BP网络训练所需的时间要短得多.因此RBF神经网络具有很好的实用价值,为虫情预报系统提供了新思路、开辟了新途径.
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| 关 键 词： | 预报 人工神经网络 径向基函数 棉叶螨 |
RBF Network Model for Cotton Leaf Acarus Occurrence Trends Forecasting |
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| LIU Jing-ran
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MA Ying-jie
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LEI Xiao-yun
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WANG Zhe.RBF Network Model for Cotton Leaf Acarus Occurrence Trends Forecasting[J].Water Saving Irrigation,2009(5). |
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| Authors: | LIU Jing-ran MA Ying-jie LEI Xiao-yun WANG Zhe |
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| Institution: | College of Hydraulic and Civil Engineering;Xinjiang Agricultural University;Urumqi 830052;China |
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| Abstract: | Using the method of RBF network and MATLAB toolbox,combined with the meteorological data of the average temperature,the lowest temperature,the relative humidity and the rainfall amount,the RBF neural network system is established to forecast the cotton leaf acarus degree in Shihezi areas of Xinjiang.The forecast accuracy of the system is proved through examples and comparison with normal BP network.Time test shows that the training time of RBF network is 0.079 s,which is much shorter than that of BP network... |
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| Keywords: | forecast artificial neural network radial basis function cotton leaf acarus |
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