The BPNN model of Bayesian regularization method was adopted to create the adaptivity and generalization of BPNN.
文中采用贝叶斯正则化与BP网络结合的方法，建立动态前馈校正模型。
The constringency speed and generalization ability of optimized BPNN model are better than that of simple BPNN model, and the simulation result is close to reality.
遗传算法优化的BP神经网络在收敛速度和泛化能力上都较简单的BP神经网络要好，模拟结果更接近于真实值。
After the comparison of optimized BPNN model and simple BPNN model, the result shows that, it is completed feasible to use optimized BPNN model in cultivated land classification work.
将优化后的BP神经网络模型和简单的BP神经网络进行比较，实验结果表明，基于遗传算法优化的BP神经网络模型在耕地分等评价工作中的应用完全可行。
Black body furnace temperature time series prediction model based on BPNN was built.
文章在神经网络的基础上，建立了黑体炉温度时序预测模型。
The experimental results on the real industrial data demonstrate that the model based on SVM achieves good performance and has less prediction errors than those of BPNN and RBFNN models.
在实际工业数据上进行的实验结果表明，支持向量机模型对丙酮纯度具有良好的预测效果，性能优于反向传播神经网络和径向基网络模型。
As complex information system usually contains large amount of attributes which can be used as the input variables of a model, it may bring about constructing a complicated BPNN.
考虑到大量的输入属性可能导致复杂的BPNN，研究了用启发式方法和并行穷举方法约简属性的方法。
As complex information system usually contains large amount of attributes which can be used as the input variables of a model, it may bring about constructing a complicated BPNN.
考虑到大量的输入属性可能导致复杂的BPNN，研究了用启发式方法和并行穷举方法约简属性的方法。
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