In order to prevent neural network learning from getting into local extreme point, artificial immune network algorithm was used to optimize neural network's parameters.
为了避免神经网络的学习过程陷入局部极值点，采用人工免疫网络优化神经网络的参数。
During the use of the artificial neural network some nodes were deleted to optimize the network based on the correlation analytical theory.
在应用人工神经网络时，采用基于相关分析法的节点删除法来优化网络结构提高网络性能。
Acordingly, it proposed that optimize the structure of neural network using genetic algorithms, so as to enhance the overall performance of disease diagnostic model.
然后文章提出用遗传算法来优化神经网络结构，从而从整体上提升疾病诊断模型的性能。
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