Based on characteristics of BP neural network which can precisely analyze multi-variable nonlinear systems using artificial intelligence, in this paper, we proposed model for predicting rubber aging.
依据BP神经网络系统能够利用人工智能的方法，准确分析多变量非线性系统的特性，采用多层向前BP神经网络系统建立起了橡胶老化预报模型。
Meanwhile, a linear regression model and a BP neural network model for predicting the springback quantity were set up.
同时，分别建立了回弹量的线性回归预测模型和BP神经网络预测模型。
Predicting the node's load information changes using the BP neural network, and establishing the prediction model based on BP neural network.
采用BP神经网络预测结点的负载变化情况，并建立BP神经网络预测模型。
Objective: To explore the prospect of predicting disease incidence of the predictive model of nonlinear time series by BP neural network.
目的：探讨ANN时间序列预测模型在疾病发病率或死亡率预测上的应用前景。
GA-BP neural network model is applied in matching and predicting the production of the gas Wells with 5.1% of the average relative error. It proves th...
利用GA - BP神经网络模型对气井产量进行了拟合和预测，拟合的平均相对误差为5.1%，表明新模型适用于洛带气田的产量递减预测。
GA-BP neural network model is applied in matching and predicting the production of the gas Wells with 5.1% of the average relative error. It proves th...
利用GA - BP神经网络模型对气井产量进行了拟合和预测，拟合的平均相对误差为5.1%，表明新模型适用于洛带气田的产量递减预测。
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