...(REG)、双因素指数平滑法(DES)、Winter模型预测方法(WIN))和径向基神经网络模型(radial basis function neural network,RBFNN)的对比来实现的.实验结果表明,基于SVM的需求预测模型预测精度明显优于其他模型,有效地降低了产品安全...
基于8个网页-相关网页
...、双因素指数平滑法(DES)、Winter模型预测方法(WIN))和径向基神经网络模型(radial basis function neural network,RBFNN)的对比来实现的.实验结果表明,基于SVM的需求预测模型预测精度明显优于其他模型,有效地降低了产品安全...
基于2个网页-相关网页
和径向基神经网络模型 radial basis function neural network
结果表明,径向基神经网络模型能有效提高预测精确度,也证明了实验方法的有效性和可行性。
The results not only show radial basis network models can increase the prediction accuracy efficiently, but also prove the validity and feasibility of these motheds.
试验结果表明,加入聚类分析的径向基神经网络模型提高了连续预测的趋势准确率,降低了时间代价,并减小了模型的复杂度。
The result of this experiment shows that the modified RBF neuro-network increases trend accuracy in sequential predicting, while debasing the cost of time and reducing the complexity of the model.
该文提出一个有效的基于径向基函数神经网络的模型和状态数据融合的汽轮发电机智能估计方法。
An efficient model based on radial basis function neural network and intelligent estimating method for data fusion of the turbine-generator is presented.
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