The neural networks structure design, learning samples and training algorithms are expounded.

阐明了神经网络状态选择器的结构设计、样本选取及训练方法。

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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。

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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。

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The researchers will also look at samples stored from 2, 000 children with learning disabilities.

BBC: Gene test for learning disabilities

Samples taken from regions of the brain important in learning and memory were tested.

BBC: Elderly