文中提出一种基于数据属性重要性排序的神经网络属性选择方法。
This paper presents a method of neural network attributes selection based on data attribute importance ranking.
提出一种基于数据属性重要性排序的神经网络属性选择方法。
This paper presents a method of neural networks feature selection based on data attributes importance ranking.
研究了BP神经网络算法对空中目标进行威胁排序的方法。
Threat sequencing for aerial target based on BP neural network is researched in this paper.
提出了一种可分性判据排序的RBF神经网络属性选择方法。
Another method of RBF neural networks attributions selection based on a separability criterion ranking is presented in this paper.
运用递阶分析方法，对本文所建立的盾构隧道和基坑工程地面变形神经网络模型中所选用的输入参数进行了敏感性分析，得出预测模型输入参数的敏感性排序。
The hierarchical analysis theory is used to analyze the sensitivity of the input parameters of the neural network model of ground deformation of shield tunnel and excavation.
运用递阶分析方法，对本文所建立的盾构隧道和基坑工程地面变形神经网络模型中所选用的输入参数进行了敏感性分析，得出预测模型输入参数的敏感性排序。
The hierarchical analysis theory is used to analyze the sensitivity of the input parameters of the neural network model of ground deformation of shield tunnel and excavation.
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