Neural Computation of the MoM Matrix Elements for Planar Configurations

In this paper a new artificial neural network (ANN) based model for the calculation of the method of moments (MoM) matrix elements is presented. Training sets that characterize the matrix elements are first constructed. These sets are then utilized to effectively train two radial basis function (RBF) neural networks to accurately estimate all the elements of the MoM matrix for any mesh used. The potential of the proposed approach is demonstrated in the case of a narrow microstrip line. The current distribution on the microstrip line produced by the trained RBF networks agrees very well with the exact distribution. In addition, the proposed ANN model is much faster than the conventional MoM procedure.     

基于人工神经网络的水洞试验装置的PID自动控制系统

在水洞试验中，通过水泵及收缩段的形状控制水洞的运行过程，以保证水洞的稳定运行，并保证所进行的各种试验的质量。PID调节是最常见的一种。文章给出了一种基于人工神经网络实现自学习PID控制方法。利用该方法可以较好地实现水洞的控制。     

Adaptive motion control using neural network approximations

In this paper, we present a new adaptive technique for tracking control of mechanical systems in the presence of friction and periodic disturbances. Radial Basis Functions (RBFs) are used to compensate for the effects of nonlinearly occurring parameters in the friction and periodic disturbance model. Theoretical analysis, such as stability and transient performance, is provided. Furthermore, the performance of the adaptive RBF controller and its non-adaptive counterpart are compared.     

入侵检测及网络层安全的研究

随着计算机网络的迅速发展，网络安全问题正变得日益重要。文章介绍了计算机网络系统IP层安全概况和入侵者对IP层常采用的入侵手段，以及为防止这种入侵所采取的措施。     

用于机器人轨迹定位纠正系统的回声状态神经网络研究

循环神经网络(RecurrentNeuralNetworks)是人工神经网络(ArtificialNeuralNetworks)中重要的分支,与前馈神经网络(ForwardNeuralNetworks)相比具有更好的时间序列学习能力。但长期以来其学习法一直不能脱离前馈神经网络而自成一体,回声状态神经网络(EchoStateNetworks(ESN))是打破这一局面的全新学习方法。其独特的结构,良好的短期记忆能力,方便的学习方法,不俗的非线性特性是以前循环神经网络所不可比的。本文在介绍了回声状态神经网络之后将其用于四轮机器人的位置测量系统中,有良好的表现。     

Optimal ensemble construction via meta-evolutionary ensembles

In this paper, we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to correctly classify test points, and are given extra rewards for getting difficult points right. Ensembles consisting of multiple classifiers also compete for member classifiers, and are rewarded based on their predictive performance. In this way we aim to build small-sized optimal ensembles rather than form large-sized ensembles of individually-optimized classifiers. Experimental results on 15 data sets suggest that our algorithms can generate ensembles that are more effective than single classifiers and traditional ensemble methods.     

基于事例学习的建筑结构的虚拟实现

提出基于事例学习的目标规划问题,并进一步研究了建模思想的可行性和建模方法的可操作性。利用知识工程、机器学习理论,人工智能技术来存贮和运用专家的经验,实现了在虚拟环境中建筑结构设计、施工,设备的仿真试验,并可对初学者或尚无经验的设计、施工者进行培训学习。该项研究为目标规划问题开辟了基于事例学习的模型生成途径。     

Disorder effects on the strain response of model polymer networks

Molecular dynamics simulations are used to investigate polymer networks made by either end-linking or randomly crosslinking a melt of linear precursor chains. The resulting network structures are very different, since end-linking leads to nearly ideal monodisperse networks, while random crosslinking leads to polydisperse networks, characterized by an exponential strand length distribution. Networks with average strand length 20 and 100 were generated. These networks were used to study the effects of disorder in the network connectivity on observables averaged either over the entire network or selected sub-structures. Heterogeneities in the randomly crosslinked networks cause significant differences in the localization of monomers, however, neither the localization of crosslinks nor the microscopic strain response are significantly affected. Compared to end-linked networks, randomly crosslinked networks have a slightly increased tube diameter, and as a result a slightly decreased shear modulus, but otherwise identical stress-strain behavior. For the investigated systems, we conclude that the microscopic strain response, tube diameter, and stress-strain relation are all insensitive to the heterogeneities due to the linking process by which the network were made.     

3COM交换机技术及应用

本文介绍了3COM Superstack ⅡSwitch 3300 的主要特性及其在局域网中的实际应用，评述了冗余网络的构造等问题。