Secondly, to extract learning samples from the MADM problem, an approach to estimate the utility functions for attributes is presented.
其次,提出了基于属性效用函数估计的学习样本构造方法,从决策问题本身抽取学习样本。
The affection of learning samples and network parameters on prediction accuracy was discussed, the best network parameters were selected.
讨论了模型的学习样本、网络参数对预测精度的影响,选出最佳网络参数配置。
In the condition of selecting the learning samples properly, the artificial neural network has the obvious advantage in the inverse designing the electronic lens.
可以看到在较好的选取学习样本情况下,神经网络技术在电子透镜的逆设计中有着明显的优越性。
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