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GRNN

于 2016-09-02 发布 文件大小:14KB
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  本案例是采用GRNN(径向基)神经网络预测水资源量,GRNN神经网络适合于小样本、高精度预测,本实例附有数据(不全),下载者可以直接将数据更改为自己的数据便可以使用。程序中使用了交叉验证方法,使预测精度大大提高(This case is the use of GRNN (Radial Basis Function) neural network to predict the amount of water, GRNN neural networks suitable for small samples, high-precision prediction, the present example with data (incomplete), can directly download data to their own data will change can use. Procedures used in the cross-validation method, the prediction accuracy is improved greatly)

文件列表:

GRNN
....\GRNN.m,2213,2016-09-02
....\GRNN.xlsx,15748,2016-02-02

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