基于角色访问控制的办公自动化系统的研究与实现

介绍了访问控制的几种方法及特点,讨论了基于角色的访问控制方法来实现办公自动化系统中的资源共享、用户角色指派关系,讨论了利用Microsoft．NET中cache等缓存技术和．NET Framework中提供的现有技术,实现办公自动化系统中的角色访问控制。     

用神经网络分析估计斜拉桥的施工控制参数

结合一座三塔四跨预应力混凝土斜拉桥施工过程,进行用神经网络分析估计斜拉桥施工控制参数的研究。用神经网络分析估计斜拉桥施工控制参数的过程主要包括建立神经网络、计算训练样本、训练神经网络和网络仿真四部分。运用神经网络仿真计算进行斜拉桥施工监控的具体方法是,先计算当前施工状态的索力和标高,再预测下一节段的索力和标高。经过往复循环,逐一进行节段预测调整,从而指导斜拉桥顺利施工。通过对比该斜拉桥合拢后部分节段索力及主梁控制点标高的计算值和实测值可知,用神经网络分析进行斜拉桥施工监控的效果达到设计的理想桥梁线型和索力要求。     

Simulation of the mean zero-up-crossing wave period using artificial neural networks trained with a simulated annealing algorithm

The aim of this work was to develop a predictive model to forecast the mean zero-up-crossing wave periods (T _z ) for 3-hourly sea states at a location in the Pacific using artificial neural networks (ANNs). Seven multilayer ANNs were trained with a simulated annealing algorithm. The output of each trained ANN was used to estimate each of the seven parameters of a new distribution called the hepta-parameter spline proposed for the conditional distribution of T _z , given some mean zero-up-crossing wave periods and significant wave heights. After estimating the parameters of the distribution, the model was used to simulate and predict future values of T _z . Forecasting a sea state and developing the joint distribution of sea state characteristics with the help of the simulated characteristics are also discussed in this article.     

一种网络安全检测系统的设计与实现

介绍了网络和系统中存在的安全漏洞,设计了一个网络安全检测系统(NSDS),并分析了每一个组成部分的功能,给出了设计思路,最后通过一个实例检验了整个系统的性能.     

美国海军的综合作战系统

近年来，美国出于称霸全球、独步海洋的战略需要，不惜斥巨资构筑海上综合作战系统。本文详述了这方面的进展。     

抓住机遇奋发有为为实现铁路"十一五"规划良好开局而努力奋斗--在2006年全路计划工作会议上的讲话(摘要)

“十五”期间,铁路在路网建设、装备现代化、既有线提速扩能改造、投融资改革、节能、环保等方面均取得了重大成就。本世纪头20年是我国发展的重要战略机遇期,在实现区域经济协调发展、建设资源节约型、环境友好型社会和建立现代化综合交通运输体系中,铁路将充分发挥骨干作用。在“十一五”规划目标下,铁路面临着加快快速客运网络建设、强化煤炭运输通道、扩展西部路网、优化东中部路网等建设任务。2006年是“十一五”开局之年,要抓住机遇,提高计划管理水平,重点完成项目前期工作、落实建设资金、基建任务以及装备现代化等方面的工作,为实现铁路跨越式发展目标做出贡献。     

一种基于BP神经网络的机动目标跟踪算法

交互式多模型（IMM）算法是一种可以有效跟踪机动目标的滤波算法,针对其跟踪精度和计算量在很大程度上受制于模型选择和转移概率确定的问题,提出了一种利用BP神经网络修正子模型滤波结果的改进IMM算法。仿真实验表明,该方法可以使IMM算法的收敛速度加快,收敛精度提高,改善了跟踪性能,具有一定理论指导意义。     

基于LVQ 神经网络的轨道单元状态综合评判方法研究

为了有效利用多种检测数据评判轨道单元的状态,提出利用 LVQ (学习矢量量化)神经网络建立轨道单元特征参数与轨道单元分级的关联模型,通过对 TQI (轨道质量指数)、轨道几何、加速度、晃车仪、添乘仪、人体感觉的超限扣分加权得到轨道单元的量化评分指标,并利用层次分析法确定各特征参数的权系数。根据大量实测数据建立随机样本,利用聚类方法确定轨道单元状态的分级。以轨道单元的量化评分指标作为输入,以聚类得到的表征轨道单元分级的矢量量化数据作为输出,利用误差反向传播方法训练 LVQ 神经网络模型。利用新的评判方法对某线路的轨道单元状态进行评判,结果表明该方法可行、有效,为轨道单元状态综合评判提供了一条新途径。     

Strategic considerations behind the network–regional airline tie ups – A theoretical and empirical study

The paper examines the strategic vertical relationship between network and regional airlines. We develop a model to illustrate how network airlines can use the contractual relationship with regional airlines as an efficient tool to simultaneously drive out inefficient network airlines and also accommodate other cost efficient network airlines in any specific market. The model is tested on U.S. data using simultaneous and sequential choice models. We find that market size, cost differences between network airlines, as well as cost differences between network and regional airlines, are the chief determinants of the network airlines’ decisions on whether or not to serve a market with their own fleet, as well as how many regional airlines to contract with.     

Prioritizing road extension projects with interdependent benefits under time constraint

Since transportation projects are costly and resources are limited, prioritizing or sequencing the projects is imperative. This study was inspired by a client who asked: “I have tens of approved road extension projects, but my financial resources are limited. I cannot construct all the projects simultaneously, so can you help me prioritize my projects?” To address this question, the benefits and costs of all the possible scenarios must be known. However, the impacts (or benefit) of road extension projects are highly interdependent, and in sizable cases cannot be specified thoroughly. We demonstrate that the problem is analogous to the Traveling Salesman Problem (TSP). Dynamic change in travel demand during construction is another aspect of the complexity of the problem. The literature is yet to provide efficient methods for large cases. To this end, we developed a heuristic methodology in which the variation of travel demand during the construction period is considered. We introduce a geometrical objective function for which a solution-finding policy based on “gradient maximization” is developed. To address the projects’ interdependency, a special neural network (NN) model was devised. We developed a search engine hybridized of Ant Colony and Genetic Algorithm to seek a solution to the TSP-like problem on the NN based on gradient maximization. The algorithm was calibrated and applied to real data from the city of Winnipeg, Canada, as well as two cases based on Sioux-Falls. The results were reliable and identification of the optimum solution was achievable within acceptable computational time.