基于单代号网络的银行家算法

通过对银行家算法的分析,提出单代号网络的进程安全状态序列的改进算法-基于单代号网络的银行家算法,并通过具体的示例实现此算法。     

基于Java语言的GIS系统在电信网管系统中的开发应用

随着计算机和通信业的迅速发展,人们对电信网络管理系统的要求越来越高,不仅需要拓扑图的显示,还要求系统能进行快速的故障定位,所以要求网管系统能与GIS系统结合.本文介绍了基于java语言的GIS系统的开发过程,及如何将GIS集成到综合电信网管系统中,并就实际开发中出现的问题提出相应的解决方案.     

科技期刊信息化建设的思路与实践

面对信息化时代带来的机遇和挑战，科技期刊如何应对，以适应潮流的发展，满足更多科技工作者的需求，抓住广大读者的需求，近而提升科技期刊的影响力。文章通过对《航天器工程》期刊编辑部信息化建设和网络建设，结合实践经验，对科技期刊信息化建设进行了分析。     

关于网络伦理问题的研究与思考

人类进入21世纪，人们感受到了信息技术给人类的交往、学习、工作和生活带来极大便利，促进了人的全面发展和社会进步。但也出现了网络“道德真空”和“道德沦丧”，因此关于网络伦理问题的研究也就摆在了我们面前。     

应用神经网络模型评价社保基金运营效果方法研究

社会保障基金是社会成员普遍关注的资金,他的利用关系到全社会成员的公共利益。因此,社会保障基金运用效果的评价问题一直是社会各界争论的焦点,正确评价其运用效果是值得学术界探讨的问题。运用神经网络模型对社会保障基金运用效果进行评价是对神经网络模型的应用及对社会保障基金运用效果的评价进行尝试和探讨。     

电长度测量方法探究

从电长度的概念出发，主要介绍了使用网络分析仪来实现电长度测量的三种方法，分别是频域电延迟法、时域反射法和时域传输法；针对三种不同方法分别做了试验。     

基于分布式管理架构的应用型网管系统的设计与研究

根据当前IT应用的普及情况,分析了大中型企业中网络资源管理存在的问题,研究了网管软件的相关技术并设计了一套符合当前应用需求的分布式管理架构的应用型网管系统。该系统不但可监测各类操作系统的性能,还可对数据库、WEB服务等应用服务器的性能进行监控。结合网管软件的发展动态,展示了该应用型网管系统的工程应用价值。     

Using the radial basis function neural network to predict ionospheric critical frequency of F2 layer over Wuhan

Neural networks (NNs) have been applied to ionospheric predictions recently. This paper uses radial basis function neural network (RBF-NN) to forecast hourly values of the ionospheric F₂ layer critical frequency(f_oF₂), over Wuhan (30.5N, 114.3E), China. The false nearest neighbor method is used to determine the embedding dimension, and the principal component analysis (PCA) is used to reduce noise and dimension. The whole study is based on a sample of about 26,000 observations of f_oF₂ with 1-h time resolution, derived during the period from January 1981 to December 1983. The performance of RBF-NN is estimated by calculating the normalized root-mean-squared (NRMSE) error, and its results show that short-term predictions of f_oF₂ are improved.     

弹道跟踪数据野值剔除方法性能分析

弹道跟踪数据中的野值会影响导弹目标定位精度。对用于弹道跟踪数据的野值剔除方法进行了综述。结合事后和实时两大类处理模式,分析了各野值剔除方法在理论和工程应用上的优缺点,给出了实际应用时的限制因素,建立了野值判决准则和相应的野值剔除实现步骤。仿真结果表明:野值剔除方法可以有效提高弹道跟踪数据的精度。事后处理模式中,基于格拉布斯准则的野值剔除效果最佳;实时处理模式中,基于自适应门限的五点线性预报法野值剔除效果相对较好,且时间复杂度相对较低,适合实时处理。     

An artificial neural network approach for aerodynamic performance retention in airframe noise reduction design of a 3D swept wing model

With the progress of high-bypass turbofan and the innovation of silencing nacelle in engine noise reduction, airframe noise has now become another important sound source besides the engine noise. Thus, reducing airframe noise makes a great contribution to the overall noise reduction of a civil aircraft. However, reducing airframe noise often leads to aerodynamic perfor-mance loss in the meantime. In this case, an approach based on artificial neural network is intro-duced. An established database serves as a basis and the training sample of a back propagation (BP) artificial neural network, which uses confidence coefficient reasoning method for optimization later on. Then the most satisfactory configuration is selected for validating computations through the trained BP network. On the basis of the artificial neural network approach, an optimization pro-cess of slat cove filler (SCF) for high lift devices (HLD) on the Trap Wing is presented. Aerody-namic performance of both the baseline and optimized configurations is investigated through unsteady detached eddy simulations (DES), and a hybrid method, which combines unsteady DES method with acoustic analogy theory, is employed to validate the noise reduction effect. The numerical results indicate not merely a significant airframe noise reduction effect but also excel-lent aerodynamic performance retention simultaneously.