查询词典 neural network

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 practicality of using rough set to reduce the date was discussed, in this paper, and the interval-valued continuous attribute discretization by applying self-organizing map neural network clustering was proposed, too. This article proposes a simplified indiscernible matrix's method, which reduces the example's condition attribute and eliminates the redundant information of the date. What's more, it provides the methods used to diagnosis compressor's faults based on the intelligence hybrid system by adopting the MATLAB neural network workbox. At last, the functional modules which make up into intelligence hybrid system for fault diagnosis was introduced, including: data acquisition module, date preprocessor module, date reduction module, neural network module, fault diagnosis module and fault expressing module. Here, the article also gives the flow of work of all the above modules.

论文论述了应用粗集对故障数据进行约简的可行性，并应用自组织映射神经网络的聚类功能，来实现连续属性值的离散化方法；给出了简化的分明矩阵法，并用该方法实现了样本条件属性的约简，消除了样本数据中的冗余信息；采用MATLAB神经网络工具箱建立了压缩机的部分故障类型的智能混合诊断系统；最后介绍了智能混合故障诊断系统的功能模块组成，各功能模块分别为：数据采集模块，数据预处理模块，数据约简模块，神经网络模块，故障诊断模块，故障解释模块；并给出了各功能模块的工作流程。

The model of Protein Secondary Structure based on the multi-modal neural network This paper proposed a multi-modal neural network predictable model that synthesizes by 7 BP neural network group in protein secondary structure prediction, this model use "profile" encoding method and "the distance" between the amino acid for the excitory input information, has carried on the prediction to the protein secondary structure prediction.

3基于多神经网络的蛋白质二级结构预测模型论文提出了一个由 7 个 BP 神经网络组合成的多神经网络的蛋白质二级结构预测模型，该模型采用&profile&编码方式和氨基酸间的&距离&为激励输入信息，对蛋白质二级结构进行了预测。

Fifth, it is very promising to combine neural network or fuzzy neural network and adaptive control theory into a adaptive neural network system, aiming at solving the problems of non linearity and nondetermination.

第五，为了较好地解决系统非线性、不确定性的问题，将神经网络、模糊神经网络与自适应控制理论相结合形成自适应神经网络系统是一条有广阔前景的途径。

Now she was hungry and angry.She began to smoulder.

现在她又饿又气，她开始流露难以抑制的怒火。

You have placed our iniquities before You, Our secret sins in the light of Your presence.

诗90：8 你将我们的罪孽摆在你面前、将我们的隐恶摆在你面光之中。