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Rain fall predict and comparing research based on Arcgis and BP neural network

机译:基于ArcGIS和BP神经网络的雨落预测与比较研究

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Based on the data of the rainfall from 24 base stations on the area of Chao River Basin in the near 54 years (range from 1958 to 2012), the estimation is carried out by using Arcgis kriging interpolation and BP algorithms. And try to do the error analysis and the consequences comparing of these two results in the use of statistical approach. It is surely an innovative study which applies the advanced mathematical method in the rainfall research in the environmental field. After a serious of complicated data processing, the final conclusion is that it is feasible to apply BP neural network model to the forecast of rainfall, which is the correct method with high accuracy rate.
机译:根据在近54岁的超河流域地区的24个基站的降雨数据(从1958年至2012年的范围),通过使用ArcGIS Kriging插值和BP算法进行估计。并尝试进行错误分析,并在使用统计方法时比较这两项的后果。它肯定是一个创新研究,适用于环境领域的降雨研究中的晚期数学方法。在严重的复杂数据处理之后,最终结论是将BP神经网络模型应用于降雨预测是可行的,这是具有高精度率的正确方法。

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