查询词典 neural network

The feasibility of neural network application to asphalt concrete pavement performance forecast is set forth. Three main environmental factors-traffic, rainfall, temperature, which can lead to the direct change of pavement performance are used as the input layer of neural network. The performance indexes of asphaltum concrete pavement, i.e. dilapidation rate, smoothness, deflection, friction coefficient are used as output layer. The relation between environment factor and pavement performance is acquired by introducing the module of BP Neural Network in MATLAB.

阐述了应用BP神经网络进行沥青混凝土路面使用性能预测的可行性，以环境因素，即交通量、降雨量、温度等3个直接使路面性能发生变化的主要因素作为BP神经网络的输入层，以沥青混凝土路面的破损率、平整度、弯沉值、摩擦系数等4项性能指标作为输出层，采用MATLAB语言中的BP神经网络模块进行自学习，得出环境因素与路面使用性能之间的关系。

The micro vehicle rear axle of car main gear box noise question became the worker matter of concern. In this paper, the micro vehicle rear axle of car main gear box noise performance present situation and the traditional assessment method are discussed, and the general BP neural network and the Levenberg-Marguardt algorithm are introduced in detail. Improves the BP neural network using the LM algorithm, at present is trains the neural network the quickest algorithm.

微车后桥主减速器噪声问题成为工作者所关注的问题，本文介绍了后桥主减速器噪声性能现状及传统评价方法，阐述了BP神经网络的一般算法，并详细介绍了Levenberg-Marguardt算法，利用LM算法来改进BP神经网络，目前是训练神经网络的最快算法。

For the limitations of traditional algorithms that can not be reasonably accurately predict the traffic, we have adopted BP neural network and curvilinear regression algorithms. First, we use BP neural network to train on historical data and then use the curve of regression to predict various factors, and then forecast data into the trained BP neural network which has been trained well, you can get future traffic forecasts.

针对以上传统算法的局限性，采用BP神经网络与曲线回归耦合算法，用BP神经网络对历史数据训练，利用曲线回归对各因素待测年份之值预测，将各因素的预测值带入已训练好的BP神经网络中，即可得到未来交通量的预测值。

A new finger-print recognition method using pulse-coupled neural network s;2. Image segmentation based on pulse-coupled neural network ;3. The principle of pulse-coupled neural network used for determining the optimum route is analyzed.

分析了脉冲耦合神经网络的路径寻优原理，针对交通诱导系统的要求提出了脉冲耦合神经网络的简化方法和应用模型，给出了基于脉冲耦合神经网络简化模型的最短路径的算法。

The experimental results indicate that the LMBP neural network has higher classification rate, more rapidly converge velocity by comparing with other improved BP algorithm and the Radial Basis Function neural network. Through the experiments of recognizing the sonar image polluted with Gaussian noise, it is proved that the LMBP neural network has good stability and better anti-noise performance.

通过与标准BP算法和几种常用改进型BP神经网络以及径向基函数网络比较，验证了用LMBP神经网络作为声纳图像识别系统中的分类器，能够提高图像的识别率，加快网络的收敛速度，通过对受不同程度高斯白噪声污染的声纳图象的识别，验证了其性能稳定，具有较好的抗噪声性能。

Based on analyzing regression analysis, neural network and the least square support vector machines that the three soft computing methods fitting for data fitting, in the paper try to use nonlinear regression analysis, the BP neural network based on Levenberg-Marquardt training algorithm, radial basis function neural network on orthogonal least square training algorithm and least square support vector machines for tracking the position of glass plate.

本文在分析适于数据拟合的回归分析、神经网络、最小二乘支持向量机这三种"软计算"方法的基础上，尝试将非线性回归分析方法，基于Levenberg-Marquardt算法的BP神经网络，基于正交最小二乘训练算法的径向基函数神经网络和最小二乘支持向量机应用于玻璃板位的跟踪中。

It is suggested that physiographic features, which are ignored in current neural network models, can be and should be put into the neural network learning mechanism. This, together with hydrological features, would enable the neural network models to remedy the limitations mentioned above.

本研究提出一个新的解决方案，将集水区地文特徵参数导入类神经网路的学习机制内，使模式能够同时考量地文与水文因子来进行水特徵的推估，以突破类神经网路模式现有的应用限制。

First, the paper introduces the sturcture of feedforward neural network and classical back-propagation learning algorithm, then systematic analysis and reserch are made to the various learning methods of RBFNN(Radical Basis Function Neural Network). The idea and algorithm frame of evolution strategy are presented and introduced to the learning algorithm of BP Neural network to improve the performance of it.

本文首先阐述了前向神经网络的结构以及经典的反向传播学习算法，尤其是对RBF网络的各种学习算法进行了比较系统的分析研究，然后又介绍了进化计算的思想和算法框架，并把这种算法思想引入到BP网络学习思想中去对BP算法进行了改进。

In chapter 2, we firstly introduce the model of a discrete-time neural network with generalized input-output function. The model generalizes the input-output function in transiently chaotic neural network to a class of continuous, differentiable and monotone increasing functions. Secondly we study the uniformly asymptotical stability of equilibrium in the non-autonomous model. Finally, several examples and numerical simulations are given to illustrate and reinforce our theories. In chapter 3, we firstly introduce a specific class of discrete-time neural network models with sinusoidal activation function.

在本文的第二章中，首先介绍了一类具有广义输入输出函数的非自治离散神经网络模型，该模型把瞬时混沌神经网络模型中的输入输出函数推广到了一般的单调递增且连续可微的函数；其次，利用Schauder不动点原理和利用Lyapunov函数逆定理依次证明了模型平衡点的存在性和该模型在时变权值下的一致渐近稳定性；最后，对几个具体的例子进行数值模拟，数值模拟的结果更好地说明了我们的结论。

The engine monitor requires accurate predictions of rational velocities. A prediction model is constructed on the basis of flat neural network A fast recursive algorithm is used to improve the learning speed by forgetting factor. Accordingly, the present neural network algorithm leads to considerable reduction of effort in network weighting matrix as well as increase of self-learning and adaptability of neural network algorithms to nonlinear and nonstationary systems.

发动机监测器以精确的转速预测为前提，通过构建扁平化神经网络预测模型，并根据遗忘因子思想改进快速递推算法，既减少网络权矩阵的计算量，又充分发挥神经网络算法对非线性和非平稳系统的自学习能力。

Neither the killing of Mr Zarqawi nor any breakthrough on the political front will stop the insurgency and the fratricidal murders in their tracks.

在对危险的南部地区访问时，他斥责什叶派民兵领导人对中央集权的挑衅行为。

In fact,I've got him on the satellite mobile right now.

实际上 我们已接通卫星可视电话了