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。
In order to validate character validity, use NearestNeighbor (NN) and probabilistic neural network (PNN) classification identify target, gain content identification probability.
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；
Secondly, the profile and layer of the damaged member is also determined by probabilistic neural network with input of the normalized damage-signal index.
将人工神经网络（ANN）、广义猫映射及概率统计等知识相结合构造了一种图像空间域水印算法。
The paper, by adopting jointly Artificial Neural Network (ANN), general Amold mapping, and statistical methods, intends to formulate an algorithm based on image spatial domain watermark.
研究结果表明，该模型判别预测结果与人工神经网络模型及模糊概率模型的判别结果及实际岩爆情况较吻合。
The results show that the results predicted by Bayes model are both in good agreement with the practical conditions and the results obtained from the neural network model and fuzzy probability model.
研究结果表明，该模型判别预测结果与人工神经网络模型及模糊概率模型的判别结果及实际岩爆情况较吻合。
The results show that the results predicted by Bayes model are both in good agreement with the practical conditions and the results obtained from the neural network model and fuzzy probability model.
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