A fast method for spectrum analysis and interpolation using artificial neural network (NN) for the microwaves surveying system is studied.
本文研究了在微波探测系统中，利用人工神经网络做谱分析和插值的快速方法。
At the same time, we used relevance feedback and machine learning used in image retrieval. K-NN, BP neural network and support vector machine classifiers were used in experiments.
同时本文将机器学习和相关反馈结合起来用于图像检索，在实验中使用了K -NN、BP神经网络和支持向量机分类器。
Software based on neural network(NN) to compensate machine tools therm al deformation is studied.
研究了以神经网络（NN）为模型的软件补偿不同机床热误差。
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 first modeling approach is artificial neural network (NN).
第一种建模方法为人工神经网络模型。
Neural network (NN) is product of simulation of how-to-manage-information in human brain.
神经网络是对人脑的信息处理方式进行模拟的产物。
Based on the theory of integrated neural network, a hybrid integrated NN fault detection method is introduced in this paper. Its structure and arithmetic are fully discussed.
基于集成神经网络故障诊断理论，提出了一种混合型集成神经网络故障诊断方法，阐述了其结构和算法。
Then a genetic neural network for layout sub-problem is produced with GA and NN integrated together.
结合遗传算法，构造了布局子问题的遗传神经网络算法。
Nonlinear neural network (NN) control strategy, which was certified the high capacity of approximation, is adopted to control this typical nonlinear system.
本研究采用神经网络控制来解决这类非线性系统的控制问题。
A collateral controller based on BP neural network (NN) and PID was designed for fatigue tester system.
针对疲劳试验机控制系统，设计了基于BP神经网络和PID的并行控制器。
To solve the problem of modeling temperature control in the fermentation process, a neural network nonlinear auto regressive moving average(NN-NARMA) modeling method for nonlinear system is proposed.
针对生物发酵过程中温度控制难以建模的问题，基于非线性自回归滑动平均（NARMA）模型，设计了神经网络自回归滑动平均（NN-NARMA）模型。
The neural network (NN) models can be used to enhance the prediction of rolling parameters instead of traditional mathematical models.
用神经网络模型代替传统的数学模型，达到提高轧制参数预报精度的目的。
The using patterns of NN(neural network)in fault diagnosis are researched. The way of NN(neural network)in fault diagnosis are discussed.
本文研究了神经网络在故障诊断中的运用方式，探讨了故障诊断的神经网络方法。
The learning rate is an important parameter for the learning process of a neural network (NN) which influents the stability and quickness of the NN.
学习速率是控制神经网络学习过程的一个重要参数，影响神经网络的稳定性和快速性。
A novel adaptive support vector regression neural network (SVR-NN) is proposed, which combines respectively merits of support vector machines and a neural network.
一种新的自适应支持向量回归神经网络(SVR - NN)提出，它结合了分别支持向量机和神经网络的优点。
The experiment shows that with merging the Object Oriented concept and symbol logic, the Intelligent Neural Network system Theory provides a way to build a big, complex NN system.
实验表明，智能神经网络系统组成原理将面向对象、符号逻辑融于神经网络中，提供了构造功能完备的智能系统的途径。
In this paper, the model structure and the application of Radial Basis Function Neural Network (RBF NN) to fault diagnosis of power transformer is presented.
研究了径向基函数(RBF)神经网络的模型结构及其在电力变压器故障诊断中的实现方法。
Secondly, Neural Network (NN) model was built up to predict ultimate bond strength between the rebar and corroded concrete.
其次，建立了受腐蚀钢筋混凝土极限粘结力的神经网络预测模型。
A classical Back Propagation Neural Network (BP NN) has been developed to solve the same problem for comparison.
并应用传统的BP神经网络解决同样的问题以进行比较。
The Neural Network(NN) is widely applied to many fields for its unique structure and the method of managing information.
人工神经网络独特的结构和处理信息的方法使其在实际应用领域中取得了越来越显著的成效。
Using Genetic Algorithms (GA) to train Neural Network (NN), the weight and structure of NN is optimized at the same time.
对神经网络采用改进的基因遗传算法进行训练，可以实现神经网络权值和结构的同时优化。
In this paper, a method for analysing geological data with NN (Neural Network) and NNES (Neural Network Expert System) is presented. This method can work out the non-linear geological problem.
本文提出利用人工神经网络和神经网络专家系统的方法分析地质数据，从而更好地解决地质数据处理中的非线性问题。
Following the neural-network (NN) study method in this paper, the quality of the other schemes of the same product after learning the results of fuzzy decision can be judged efficiently.
而在此提出的神经网络学习方法，只要对已有方案的模糊决策结果进行学习，就能得到同类产品其它方案满足于总体设计目标准确的隶属度值。
Following the neural-network (NN) study method in this paper, the quality of the other schemes of the same product after learning the results of fuzzy decision can be judged efficiently.
而在此提出的神经网络学习方法，只要对已有方案的模糊决策结果进行学习，就能得到同类产品其它方案满足于总体设计目标准确的隶属度值。
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