局部网络

Because of appearing empty aggregates in the time zone (the time zone do not include the information), we only establish the indeterminate grey differential equation according to the approximate condition of the differential equation.

利用灰色微分方程中的最小二乘估计参数：进而得到灰色神经网络初始的权值及阈值，这样使初始的权值和阈值更接近准确值，克服了以往BP网络中初始权值的随机性和不确定性，减少了网络的训练次数，提高了网络收敛速度和输出的精度，为避免网络训练陷入局部极小值也起到了重要的作用。

Through analysing muddleheaded time alignment, build the network of the 3 make a present of before the layer that has many concealed node, be based on extensive to change a gender to consider to use lop algorithm to train, in node of concealed of part of the expunction on the foundation that assures to forecast precision in order to reduce network complexity, the overall situation that uses genetic algorithm to have searchs actor ability to train a network afresh, benefit appliance has algorithm of BP of the local ability that find actor to train this network again.

通过分析混沌时间序列，建立具有多个隐节点的3层前馈网络，基于泛化性考虑采用剪枝算法练习，在保证猜测精度的基础上消去部分隐节点以降低网络复杂性，利用遗传算法具有的全局寻优能力重新练习网络，利用具有局部寻优能力BP算法再次练习该网络。

It has become one of the important tasks in the study on modern electric system. At first, this text has briefly introduced meanings, the current development and the main methods which the electric load forecasting are used. This paper aimed at the floatability which the load data had and the nature that neural networks model is easy to fall into part infinitesimal value and low iterative speed, this paper proposed a method based on neural networks and SVM. SVM can dispel the less summation and the larger single point errors of neural networks, and the neural networks could dispel the simplification of the model of the vector support machine.

本文首先介绍了电力系统负荷预测的意义、发展现状和主要方法；针对负荷数据具有浮动的特点以及神经网络模型算法容易陷入局部极小和迭代速度较慢的缺点，提出了一种基于神经网络和支持向量机的混合负荷预测方法，此方法能通过支持向量机消除神经网络的总和较小但单点误差较大的不利现象，而神经网络消除了支持向量机的模型简单问题。

A network with different topologic configurations is needed for flatness pattern recognition when strip width is changing, in this case the large learn assignment, slow convergence and local minimal in the network are observed, in order to solve these problems, first, a flatness pattern recognition GA BP network model with only 6 input and 3 output signals has been established based on Legendre orthodoxy polynomial, which is not only simple in structure but also is of clear physical meaning.

针对板宽变化时需要不同拓扑结构的神经网络才能完成板形模式识别任务，网络学习工作量大，网络存在收敛速度慢，易陷入局部极小等结构性能不佳的问题，首次建立了以勒让德正交多项式为基模式的只用 6个输入信号、3个输出信号的板形模式识别 GA- BP网络模型。

The data in LLE are optimized using the small world algorithm, and the shortest path and the local neighbor set clustering coefficients are used as the local parameters. As a result, the problem of the embedding distortion using only local linear patch of the manifold to define neighborhood in Euclidean space is effectively solved. Three groups of standard data sets are selected to test and to compare the efficiency and robustness of SLLE and LLE.

将复杂网络算法引入到流形学习中，利用小世界算法对LLE算法进行数据优化，并以最短路径和局部集群系数作为局部优化参数，解决了数据点不规则时以欧氏空间作为邻域判别标准在构建局部超平面造成嵌入结果扭曲的难题。

The fault diagnosis of Fuzzy ANN is realized by the Neural Network Toolbox of MATLAB. The result is proved valid, but also proved easy to be trapped in the local extremum.

这里以BP网络为应用模型，把模糊化后的故障特征参数作为网络的输入样本，对样本数据训练、仿真，应用MATLAB提供的神经网络工具箱函数实现了模糊神经网络对设备故障的诊断，结果证明了该诊断模型的有效性，但也暴露出BP算法易陷入局部极值的弱点。

This paper designs an ubiquitous network architecture based on social network analysis and a network simulation platform, speciously focuses on management,organization and cooperation of social network analysis,uses Multi-Agent technology to design architecture, simulation platform,virtual organization,agent acting as manager or worker,and uses the XML to expend th.

针对泛在网络面临局部自治性、异构性、复杂性、混沌性等问题，提出一种基于社会网络分析的泛在网络体系架构及网络仿真平台，并进行原型系统实现。

Aiming at the disadvantage of conventional BP neural network, such as selecting parameter values by the empirical method, slow convergence speed and easy trap into local minimum points, this paper designs an improved BP neural network system. In order to improve the network convergence rate and reduce the training error, this paper optimizes the initial connecting weight value of neural network by the use of ant colony algorithm and trains artificial neural network by Levenberg-Marquardt algorithm.

针对常规BP神经网络参数的经验式取值方法以及收敛速度慢，容易陷入局部最小点等缺陷，设计了一种改进的神经网络系统，利用蚁群算法优化神经网络连接权初值，并采用LM算法对人工神经网络进行训练，提高了网络的收敛速度，降低了训练误差。

After some generations the population diversity would be greatly reduced and the algorithm might lead to a premature convergence to a local optimum. To circumvent these shortcomings, the chaotic dynamic system is introduced in the studies of chemometric algorithms. The chaotic mapping itself is very sensitive to the initial state in a manner similar to the statistical randomness but with its underlying patterns appearing to be phantasmagoric in a deterministic style.

神经网络是一个优异的非线性建模工具，但其突出的缺点就是潜在的预收敛到局部最优点或过拟合导致的错误预报模式；遗传算法用于优化过程其目的是为了避免陷入局部最优点，但事实上由于在传统遗传算法的进化过程中只有少数最好的成员被保留下来用于产生子代成员，经过一定代数的进化后群体成员的多样性就会显著下降，也很可能过早收敛到局部最优点。

The algorithm searches the minimal energy cost path by using a local broadcast rouging scan in constrained ad hoc network. It just need to know local topology and link information instead the whole topology and links'status.

提出一种分布式局部广播路由算法，网络节点只需维持本地网络拓扑信息和本地链路的状态信息，而不必了解整个网络的拓扑结构和网络中其它链路的状态。

On the other hand, the more important thing is because the urban housing is a kind of heterogeneity products.

另一方面，更重要的是由于城市住房是一种异质性产品。

Climate histogram is the fall that collects place measure calm value, cent serves as cross axle for a few equal interval, the area that the frequency that the value appears according to place is accumulated and becomes will be determined inside each interval, discharge the graph that rise with post, also be called histogram.

气候直方图是将所收集的降水量测定值，分为几个相等的区间作为横轴，并将各区间内所测定值依所出现的次数累积而成的面积，用柱子排起来的图形，也叫做柱状图。