Probabilistic neural network (PNN) model is a kind of artificial neural network, which is simple in structure, easy for training and widely used.
概率神经网络(PNN)是一种训练速度快、结构简洁明了、应用广泛的人工神经网络。
Secondly, the profile and layer of the damaged member is also determined by probabilistic neural network with input of the normalized damage-signal index.
然后将构件损伤引起的标准化的损伤信号指标输入概率神经网络，进行损伤构件所在侧面及所在层的判定；
Using an example, a method based on probabilistic neural network technique is introduced, which aims at prediction of petrophysical parameters for reservoir.
通过实例介绍了利用一种概率神经网络技术预测储层物性参数的方法。
In the modeling of the structure, the wavelet probabilistic neural network was used to recognize the control chart patterns and estimate the abnormal patterns parameters.
在模型构造中，采用小波概率神经网络进行控制图的模式识别和控制图异常模式的参数估计。
In order to validate character validity, use NearestNeighbor (NN) and probabilistic neural network (PNN) classification identify target, gain content identification probability.
为了验证特征的有效性，使用最近邻及概率神经网络分类器进行了目标识别，得到满意的识别率。
The generalization error of Support Vector Machine is approximately equal to that of Probabilistic Neural Network. And Support Vector Machine is easier to use than Neural Networks.
支持向量机的分类误差与概率神经网络相近，但支持向量机的使用较概率神经网络简单。
Probabilistic neural network is good at classifying, we proposed a new method for aeroengine fault diagnosis based on PNN, and it can diagnose three typical aeroengine rotor fault accurately.
鉴于概率神经网络良好的分类性能，提出一种基于PNN的飞机发动机故障诊断方法，成功对三种典型飞机发动机转子故障做出了正确诊断。
Make use of available experimental data of LY12CZ aluminum alloy, a probabilistic neural network was developed to classify the maximum corrosion depth ranges based on the material failure mode.
运用LY12CZ的腐蚀实验数据，根据高强铝合金的失效模式（点蚀-晶间腐蚀-剥蚀），建立了对最大腐蚀深度分类的概率神经网络模型，输出结果与实验数据比较吻合。
Make use of available experimental data of LY12CZ aluminum alloy, a probabilistic neural network was developed to classify the maximum corrosion depth ranges based on the material failure mode.
运用LY12CZ的腐蚀实验数据，根据高强铝合金的失效模式（点蚀-晶间腐蚀-剥蚀），建立了对最大腐蚀深度分类的概率神经网络模型，输出结果与实验数据比较吻合。
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