概率神经网络算法与地震属性分析。
The arithmetic of NN probability and seismic attribute analysis.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
This paper presents an efficient training algorithm for probabilistic neural networks using the minimum classification error criterion.
提出了一种基于最小分类错误准则的概率神经网络的训练算法。
This paper presents a training algorithm for probabilistic neural networks using the MCE criterion.
当应用在概率神经网络分类时，可对其固有的两个缺点都有所改善。
When applied to the Probabilistic Neural Networks, the approach improves its two inherent shortcomings.
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。
Using an example, a method based on probabilistic neural network technique is introduced, which aims at prediction of petrophysical parameters for reservoir.
最后，利用概率神经网络技术进一步从关联故障特征中辨识出初始故障源。
Finally, PNN method is used to identify the primary fault sources from the features of correlative faults.
说明用概率神经网络对基于空间桁架传力机理的桩承台进行损伤识别是可行的。
It is feasible that using PNN to identify damage of pile cap which is based on the space truss load transfer mechanism.
基于径向基概率神经网络，提出一种扫描工程图纸图像分割后的图形符号识别方法。
A novel graphic symbol recognition approach of engineering drawings based on radial basis probabilistic neural networks (RBPNN) is proposed.
但是我们的试验结果表明，概率神经网络可以成功的用于联机手写字符的识别问题。
But the results have shown that the HMM neural network can work successfully on the recognition of handwritten characters.
在对径向基概率神经网络进行理论分析基础上，采用减法聚类方法确定它的隐中心矢量。
On the basis of analyzing RBPNN in theory, subtractive clustering is used to determine its hidden centric vector.
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。
Probabilistic neural network (PNN) model is a kind of artificial neural network, which is simple in structure, easy for training and widely used.
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。
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.
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 the modeling of the structure, the wavelet probabilistic neural network was used to recognize the control chart patterns and estimate the abnormal patterns parameters.
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.
将改进的概率神经网络(PNN)用于奇异摄动系统的实时状态估计，注重针对系统快变部分的滤波。
Probabilistic Neural Networks (PNN) is improved and used on line to estimate the states of singular perturbed systems, especially to the fast states of the systems.
在特征提取的基础上，进一步利用径向基概率神经网络(RBPNN)分类器，实现了掌纹的自动识别。
Furthermore, on the basis of feature extraction, by utilizing the Radial basis Probabilistic Neural Networks (RBPNN), the palmprint recognition task could be implemented automatically.
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.
发现基于概率神经网络的结构损伤定位方法能够正确识别单一位置损伤，且组合参数作为输入指标时的识别效果更好。
The result indicates that probabilistic neural networks can localize the single damage correctly, and the networks with the compounded index show better effectiveness.
比较而言，学习矢量量化网络在分类能力和训练成本方面更胜一筹，而概率神经网络则在计算负载和易用性方面更好一些。
By comparison, LVQ network was better than the others in classification ability and training cost, and PNN network in computation load and easy use.
通过人工引入故障，对某大楼中央空调运行的现场测量，测量结果经处理后输入概率神经网络，经运算后对中央空调进行故障检测与诊断。
The fault detection and diagnosis were implemented on the basis of field experiment test for a real building air conditioning, which was artificially introduced into series faults one by one.
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。
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.
比较而言，学习矢量量化网络和概率神经网络在分类能力方面要比反向传播网络好一些，概率神经网络在计算负载方面比学习矢量量化网络要更胜一筹。
By comparison, LVQ network and PNN network are better than BPN network in classification ability, and PNN network is better than the others in computation load.
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.
评述了灰色预测方法，概率统计方法，人工神经网络方法和可靠度函数分析四种国内外正在研究和使用的方法。
A review is made of the four methods being studied and used in China and other countries: gray prediction, probabilistic statistics, artificial nerve network, and functional analysis of reliability.
针对疲劳裂纹扩展寿命失效概率计算的复杂性，提出基于神经网络响应面的可靠性分析方法。
In response to the complexity of calculation for failure probability regarding fatigue crack growth life, a method for reliability analysis based on neural network response surface was presented.
文章从单变量模型、多变量模型、条件概率模型以及神经网络模型等最新模型介绍了国外对财务困境预测模型的研究；
The paper introduces the new studies on single-variable model, multi-variable model, conditioning probability model and nerve network model in foreign countries.
本文主要涉及的不确定推理模型包括主观贝叶斯的概率推理模型，可信度理论推理模型，证据理论及其改进推理模型以及神经网络推理模型。
In the paper, the models of uncertain reasoning are focused, such as the reasoning model of Bayes probability, Reliability theory, D-S evidence theory and Neural Network.
在控制系统中，将贝叶斯概率引入到模糊rbf神经网络中，增强了系统的推理能力，提高了飞机各个航道位置的模拟伺服精度。
In the control system, Bayes probability is introduced in the fuzzy RBF neural network and it intensity the inference ability and increase the servo precision.
信用风险是商业银行面临的主要风险，信用风险的度量模型有专家判断法、信用评分法、神经网络分析法以及现代违约概率模型等。
Credit risk is the main risk taken by commercial Banks. Credit risk measurement models include Expert Judgment, Credit Scoring, Neural Network Analysis as well as Modern Default Probability model.
本文应用HMM概率模型和神经网络结合，对联机手写数字和数学符号进行识别。
We recognize on-line handwritten figure and some mathematic characters using the HMM neural networks, and achieve a better result.
应用推荐