神经网络具有良好的记忆、归纳和学习能力，对难以用数学方法建立精确模型的信息、工艺等能够进行有效地预测建模。
The neural network has the abilities of memory, induction & study , it can effectively build forecasting model for information & technics which are difficult to be built into an exact math model.
因此，基因调控网络较精确的模型应该包括随机噪声。
Therefore, gene regulatory network should be described by more accurate models which include random noise.
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.
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