Classification of rainfall variability by using artificial neural networks.
用人工神经网络法对降水变率进行分类。
The results of experiments and analyses show that the new approach is not only simpler and easier, but also is applicable to many neural networks and many classification problems.
实验和分析表明，这种方法简单可靠，对许多神经网络和模式分类问题效果明显。
To solve the problem of automatic classification for ultrasound placenta images, we put forward an algorithm based on adaptive multiple neural networks.
针对胎盘超声图像自动分级这一临床应用问题，提出一种基于自适应多神经网络的分级算法。
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。
To solve the classification of dynamic signal, this paper proposed a feedback process neural networks model and classification methods based on this model.
针对动态信号模式分类问题，提出了一种反馈过程神经元网络模型和基于该模型的分类方法。
The spatial information of the image and evidence theory is applied to classification of remote sensing image based on neural networks.
把影像的空间信息融入分类决策，提出了一种基于证据理论与神经网络的遥感影像分类方法。
A learning algorithm based on a hard limiter for feedforward neural networks (NN) is presented, and is applied in solving classification problems on separable convex sets and disjoint sets.
提出了基于硬限幅功能函数的前向神经网络的分类学习算法，并将其应用于可分凸集或不交集合的分类。
Different models of neural networks were trained to choose the best performance network for pump impeller imbalance fault diagnosis and classification.
选择不同的中枢网络作为最好的网络进行叶轮不平衡故障诊断和分类。
As such, neural networks have been applied to problems such as disease classification and identification of biomarkers.
例如，神经网络可以被应用到诸如疾病分类和生物标记的识别问题上。
Tongue color automatic classification, based on LVQ neural networks classifier, is proposed in this paper.
本文基于学习矢量量化（LVQ）神经网络分类器，实现了舌象分析中的舌色、苔色自动分类。
Artificial Neural Networks and Support Vector Machine were selected to test classification accuracy and the test results were analyzed.
选取人工神经网络和支持向量机进行分类准确性测试，并对测试结果做出分析。
On the basis of above analysis, the application of the BP neural networks in leak signals identification and classification is made.
在此基础上，研究了BP神经网络在泄漏信号识别和分类中的应用。
In this paper, a hybrid fuzzy neural network architecture is proposed for complex diagnosis objects. A series of fuzzy neural sub networks are integrated to perform the task of fault classification.
对于复杂的诊断对象，本文提出了一种复合模糊神经网络结构，该神经网络结构集成了一系列模糊神经子网络，来完成故障分类任务。
Compared with multivariate statistics and artificial neural networks, support vector machine based on structure risk minimization has better classification performance.
与统计分析和神经网络相比，基于结构风险最小的支持向量机有更好的分类性能。
In this paper, defects for NDT are classified with neural network which USES features extracted from signal processing. Then classification results from networks are fused with fuzzy integral.
在无损检测信号处理和特征构造的基础上，用神经网络对缺陷进行识别，然后运用模糊积分对多个神经网络的分类结果进行融合。
In this paper, data mining is applied to the credit sorting of insurance client, which used the covering algorithm on which based neural networks as the classification of clients' credit.
文中将数据挖掘应用于保险客户在信用等级的分类中，即采用了基于神经网络的覆盖算法作为客户信用评分分类器的设计算法。
Current remote sensing image classification models and algorithms commonly used statistical methods, neural networks, Bayesian and so on.
目前遥感影像分类的常用模型和算法有统计学方法、神经网络、贝叶斯等。
With the full use of computer vision and neural networks, this paper presents an automatic classification method in the stored-grain pests.
综合利用计算机视觉技术和自组织神经网络技术，实现了对粮仓害虫的无损检测。
It has payed great attention to effective training of feedforward neural networks when they are used for pattern classification.
前向网络在用于模式分类时，其网络的有效训练一直是一个受到关注的问题。
Particle swarm optimization- support vector machine classification has slightly better result than self-organizing neural networks, but the complexity of network was increased.
粒子群优化支持向量机分类效果稍好，但是增加了网络的复杂度；
A practical neural networks based classification system was discussed in this paper, in which automatic knowledge acquiring and fuzzy reasoning was realized.
讨论了一个基于神经网络处理系统，实现了推理知识的自动获取和自适应模糊推理，具有很强的实用性。
This paper combines the two aspects to recognize handwritten digits by using wavelet transform to extract feature and Adaptive Resonance Theory (ART) Neural Networks for Classification.
本文将二者结合起来，用小波变换抽取特征、用自适应共振art网络作模式分类器来识别手写数字。
It is one of the important methods of pattern recognition to apply neural networks to target classification.
应用人工神经网络进行目标识别是当前模式识别的重要方法之一。
This paper discusses the optimization of back propagaton neural networks for the grain texture feature, extraction in grain classification.
主要讨论了在谷物纹理识别中对神经网络的优化。
Real biological data experiments have shown that this classification method outperformed than single neural networks, 1-nearest-neighbor classifiers and decision trees.
实际的生物学数据实验表明该方法性能优于单个神经网络，最近邻法和决策树。
Real biological data experiments have shown that this classification method outperformed than single neural networks, 1-nearest-neighbor classifiers and decision trees.
实际的生物学数据实验表明该方法性能优于单个神经网络，最近邻法和决策树。
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