The example analysis proves that GRNN model can be used in the data processing of the disease forecasting.
实例分析证明，广义回归网络模型可以应用于疾病预测数据处理工作，并可以取得更优的分析结果。
The results show that the GRNN model constructed in this way can precisely forecast urban short-term traffic flow.
研究结果表明，构建的神经网络模型能够很精确地实时预测城市道路短期交通流。
Example with survey data and compare with BP both showed that the GRNN model makes an effective way to forecast multi-point deformation with rapid calculation and high accuracy.
实例计算与比较结果表明，GRNN模型计算快、精度高，是进行多测点非线性变形监测预报的有效工具。
Considering the non-linear behavior of the viscoelastic material according to the change of environment, the GRNN is used to make a model to predict the dynamic property of the material.
考虑到粘弹性材料阻尼性能随环境的非线性变化，运用GRNN(广义回归网络)对粘弹阻尼材料动态力学性能函数进行逼近，并构建预测模型。
A model based on general regression neural networks (GRNN) has been established to predict the end point of batch pulping cooking.
为了实现制浆蒸煮终点的精确预测，建立了基于广义回归神经网络(GRNN)的预测模型。
A model based on general regression neural networks (GRNN) has been established to predict the end point of batch pulping cooking.
为了实现制浆蒸煮终点的精确预测，建立了基于广义回归神经网络(GRNN)的预测模型。
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