ANNs

A Fault Diagnostic Method of Circuit Board Based on Magnetic Field Image and ANNs

基于磁场映像和人工神经网络的电路板故障诊断

Recognition and forecasting are two of the basic functions of the ANNs .

识别和预测是人工神经网络的两大主要功能。

Research About Color Film Emulsion Data Analysis Based on BP ANNs Model

BP神经网络模型在彩色胶卷乳剂数据分析中的应用

The Optimization of Initial Weights of ANNs Based on Improved Genetic Algorithms

基于改进型遗传算法的神经网络参数优化

Application of Two ANNs to Fault Diagnosis of Gas Chromatograph in Transformer Oil

两种神经网络在变压器油色谱故障诊断中的应用

Prediction and Optimal Control for Bioprocess Based on ANNs

基于神经网络的生化过程预估优化控制

This paper focuses on application of ANNS in the study of the karst basin and its low flow .

本文主要讨论人工神经网络在喀斯特流域及其枯水径流研究中的应用。

Artificial neural networks ( ANNs ) has a long development history and it has made great progress in recent years .

人工神经网络技术已有很长的历史，但近些年来进展非常迅速。

The results show that ANNs can be used effectively determining the delay time for AVAC systems .

结果表明ANN可以有效地用于确定HVAC系统的延迟时间。

In this paper , ANNs are applied to study of the bandgap characteristic of DGS .

本文针对神经网络在DGS滤波特性中的应用进行了研究。

The second stage consists of a combination module to mix the two individual ANNs produced in the first stage .

第二层是把第一层的两个网络输出进行组合。

The greatest advantage of ANNs is that no prior knowledge of migration behavior and separation system is needed .

人工神经元网络具有很强的非线性校正能力，其最大优点是无须对分离体系及组分的迁移行为预先予以了解。

The basic principle and method of4D geological modeling using Artificial Neural Network System ( ANNS ) are discussed in the paper .

论述了用人工神经网络系统建立储层四维地质模型的原理和方法。

A method which applied Artificial Neural Nets ( ANNs ) to evaluation synthetic economic efficiency of business firm is proposed here .

本文提出了应用人工神经经网络的ART模型进行企业综合经济效益评估的方法。

Artificial Neural Networks ( ANNs ) are parallel computational systems comprised of densely interconnected neurons .

人工神经网络（ANNs）是一个由大量相互连接的神经元组成的并行计算系统。

Support Vector Machine recognition model was also established . This paper proposes the fusion model of SVM and ANNs that have different mathematical characteristics .

本文还建立了基于支持向量机的识别模型，并将这两类具有不同数学特性的智能监测模型进行决策融合，实现对刀具磨损状态的精确识别。

ANNs Approach to Analogue Modulation Recognition

模拟调制信号的神经网络识别方法

In this paper , to take predicting the wheel-rail force as a goal , four predicting method based on ANNs are discussed .

本文以精确预测轮轨力为目的，主要讨论了基于多种人工神经网络的轮轨力预测方法，并提出一种适用大型NARX神经网络结构的训练算法。

ANNs are now being used in signal processing , medicine , control system , business , pattern recognition , speech recognition and much more areas .

如今，人工神经网络已经在信号处理、医疗、控制系统、商业、模式识别、语音识别等多个领域得到了广泛的应用。

Cross-validations of FAN model and ANNs ( Artificial Neural Networks ) were conducted on two different sample datasets .

在两个干扰性不同的样本集上，分别对FAN模型和人工神经网络模型进行交叉验证。

Fourthly , a new BP ANNS prediction model with divided pattern is constructed , and each pattern are pertinently designed .

第四，提出一种全新的分段BP神经网络预测模型。

The paper combines artificial neural networks ( ANNs ) with Kalman filter real-time adjustment technique in order to improve traditional ANNs model .

为改进神经网络模型算法，将神经网络技术与卡尔曼滤波技术进行耦合。

Based upon the characteristics of integrative interpretation of pay beds , a new method using ANNs for integrative pay beds interpretation is presented .

根据油气层综合解释的特点，提出了单井油气层综合解释的人工神经网络方法。

In this thesis , the feasible criteria of several ANNs to criticize existence of the unique global exponential stable equilibrium .

本文目的是给出判别几类神经网络存在唯一全局指数稳定平衡点的实用有效的判据。

The advantages and disadvantages were analyzed for ANNs and mathematical simulation . A foundation was kid on the establishment of cross over method .

并对神经元网络方法和数学模拟方法进行讨论，分析了两种方法的优缺点，分“互补法”的建立奠定了基础。

Efficient Mapping of ANNs on Crossed Cubes

人工智能神经网络在交叉立方体上的有效映射

The efficiency and advantage of the method is proved by the prediction results for the activity of herbicide based on the improved and traditional BP ANNs .

在人工神经网络用于除草剂化合物活性预测的研究中，和传统BP算法的对比试验显示，本文的改进BP网络具有更快的收敛速度和更高的精度。

The on-line fault diagnosis of engine was conducted using the sensor sampling data as the inputs of ANNs and the faults code as the output .

以传感器采样值作为神经网络的输入，故障代码作为输出，对电控汽油机进行在线故障诊断。

Identification results indicate that the ANNs have good numerical steadiness and robustness even if only a few nodal mode shapes with noise were obtained .

结果表明即使在只获得少量节点振型数据且含有数据误差的情况下网络仍具有较好稳定性和鲁棒性。

The performance of the ANNs is compared with that of the auto regressive models . A Study of Overprint Error in Auto - Detection

为了与传统的随机水文模型对比，选择了自回归模型。自动检测套印误差的研究