一种公交最佳路径选择方法

通过分析最短路径算法及城市公交网络的特点提出了城市公交网络换乘的实现方法.首先,针对城市公交网络构造公交网络模型.其次,根据城市公交网络特点引入公交网络的直达矩阵,并依据该直达矩阵将城市公交网络抽象表示成一个"公交网络邻接图".再次,利用最短路径算法结合城市公交抽象网络图计算,得出最少换乘次数和可能的换乘站点.最后,利用所建立公交网络模型及所得换乘次数和可能的换乘站点进行计算,得到了综合考虑最小换乘和最短路径的最佳路径.并用一算例检验了该算法的有效性.     

无线可充电传感网络的多车动态路径规划

因构成无线传感器网络的传感器节点采用容量有限的电池供电,其生存时间有限,限制了网络的适用范围和发展.利用充电小车给传感器充电是解决传感器网络能量不足的一种重要方法.现有研究未考虑节点能量消耗值的随机动态变化,而这是传感器节点能耗的重要特征.本文综合考虑传感器节点的距离、覆盖面积和剩余生存时间,提出了一种能使小车实现自动...     

基于递归搜索的公交换乘算法研究

在城市的公共交通网络中,公交换乘是乘客出行的一个重要的问题。随着城市公交规模的不断扩大,有相当部分的出行难以直达,乘客必须换乘才可到达目的地。在研究公交换乘的最优路径算法时,有必要先了解乘客出行时所考虑的因素,通过对乘客出行心理、行为的研究来确定模型的优化目标和约束条件。文中从换乘算法、出行时间、出行距离等方面进行分析,在综合考虑相关因素的情况下,加权平均得出了一种最小换乘次数为主的广度优先算法,并应用于武汉号码百事通系统中。     

遗传算法在移动机器人路径规划的研究

针对基本遗传算法在移动机器人路径规划问题上存在的收敛速度慢以及所得路径转弯次数过多能耗大等缺点,对遗传算法进行改进,该方法利用同邻交叉方式,通过选取具有相同可行邻居结点的交叉对进行交叉操作,得到比双亲更为合适的可行路径。改进的变异方式是选择一个初始变异结点,计算它的可行邻居结点所在路径的适应度值,适应度值最优的就作为变异结点。新的适应度函数考虑了路径的距离、安全性和能量消耗等因素。仿真结果表明,将改进的交叉变异算子和新的适应度函数结合使用有助得到转弯次数较少的最优路径。     

面向物联网的深度Q网络无人机路径规划

随着无人机技术的广泛应用,基于无人机辅助数据收集的物联网架构扩展了物联网的应用范围,尤其适用于军事战场、灾害救援等极端场景。针对上述场景,该文提出一种基于深度Q网络(Deep Q-Network, DQN)框架的无人机飞行路径规划算法。该算法以无人机飞行周期内收集信息的平均信息年龄(Age of Information, AoI)为优化目标,来保证无人机收集数据的时效性。仿真结果表明,所提算法可以有效降低无人机单个飞行周期内收集数据的平均AoI。与随机算法、基于最大AoI的贪心算法、最短路径算法以及基于AoI的路径规划算法(AoI-based Trajectory Planning, ATP)相比,平均AoI分别降低了约81%, 67%, 56%和39%。该研究实现了无人机辅助物联网系统中,数据的高效、低时延采集。     

城市公交换乘数据模型研究及算法实现

人们出行时选择公共交通是常用的一种方式，本文的目的在于如何能够方便地为人们出行时选择最优的公交换乘方案。首先设计了城市公交网络模型，并分析此模型详细的数据结构，在此基础之上提出以最小换乘次数为主的广度优先搜索的公交换乘算法．并结合实际情况，对此算法进行了人性化的改进，如步行换乘、综合因素等，使得计算出来的换乘方案的实用程度大大提高，符合大多数人的出行习惯和要求。     

图规划在路径规划中的应用

随着科学技术的不断发展,机器人研究成为当今的热门话题,人们趋向于用机器人替代人类去完成一些危险的工作。而路径规划是机器人研究的难点之一。本文以机器人的运输问题为例,介绍了图规划的算法,以及如何利用图规划技术对路径规划问题进行求解。     

基于动态分段的最优公交乘车方案查询的实现

多数公交查询系统的换乘方案都是采用最短路径的算法,本文对公交线路数据采用动态分段技术进行组织与处理,结合邻接矩阵的路径查询算法,可实现获得基于最短路径、最小换乘数或是最少费用等各种最优换乘方案,提高了公交换乘方案的适用性。     

无线传感器网络中基于刚性的移动锚节点路径规划

在移动锚节点辅助定位中,锚节点通常沿着预设轨迹扫描或采用随机方式移动,当节点分布不均匀、待定位区域形状复杂时,存在锚节点冗余移动、位置冗余广播及定位性能难以确保等问题。该文提出了利用网络拓扑信息进行移动路径规划的新思路,首先利用刚性理论将网络划分为多个唯一可定位的单元,之后寻找一条遍历各单元的最短路径作为锚节点的移动轨迹,锚节点沿着该轨迹移动、依次定位各单元。大规模仿真结果表明,该策略可以有效避免锚节点的冗余移动和位置广播,灵巧适应各种布设情形,与经典的扫描式路径相比,大大降低了路径长度和位置数目。     

移动机器人路径规划方法研究

移动机器人技术研究中的一个重要领域是路径规划技术，它分为基于模型的环境已知的全局路径规划和基于传感器的环境未知的局部路径规划。综述了移动机器人路径规划技术的发展现状指出了各种方法的优点与不足，最后对移动机器人路径规划技术的发展趋势进行了展望。     

公交线路智能查询系统的设计

介绍了采用先进的语音识别和合成技术，对现有的公交公司的服务热线提出了改进方案，使服务热线更具有人性化、智能化以及快速、方便的服务。     

传输网络光缆物理路由的规划

光传输网络的突出优势就是组网,自愈环是其主要拓扑结构,网络具有自愈保护功能。本地传输网络一般按骨干层、汇聚层和接入层的功能结构组织,在层次网络结构中,如何组织光缆路由。本文利用分枝限界法解决了自愈环光缆路由的选择问题,提出了分层网络光缆路由规划的数学模型。     

多无人机协同任务规划

为解决多无人机协同规划军事目标打击的问题,基于多旅行商（TSP）数字规划理论进行路径和时间的优化。文中建立了多旅行商（TSP）数字规划模型,并根据任务性能和区域划分理论,利用退火算法求解出该模型的最优解。使用A*路径规划算法,通过编程仿真规划出了无人机的时间最优路径。结果表明,该方法较好地解决了当前无人机协同作战的目标分配问题,大幅提高了无人机协同作战的能力。     

An Energy-Aware Routing Protocol for Mobile Ad Hoc Networks Based on Route Energy Comprehensive Index

The design of energy-aware routing protocols has always been an important issue for mobile ad hoc networks (MANETs), because reducing the network energy consumption and increasing the network lifetime are the two main objectives for MANETs. Hence, this paper proposes an energy-aware routing protocol that simultaneously meets above two objectives. It first presents Route Energy Comprehensive Index (RECI) as the new routing metric, then chooses the path with both minimum hops and maximum RECI value as the route in route discovery phase, and finally takes some measures to protect the source nodes and the sink nodes from being overused when their energies are low so as to prolong the life of the corresponding data flow. Simulation results show that the proposed protocol can significantly reduce the energy consumption and extend the network lifetime while improve the average end-to-end delay compared with other protocols.     

Planning Tools for Special Networks

Hubbing has been shown to be an economical solution to the problems of providing both analog and digital special services. Digital cross-connect systems (DCS's) are an ideal vehicle for providing the hubbing function in a flexible and economic manner. However, planning hubbed networks with DCS's requires considerable analysis on a networkwide basis, a requirement difficult to carry out in a manual environment. This paper describes two strategic network planning tools that can aid network planners in determining the optimal hubbing configuration for their networks. HUBCAP (Hubbing Configuration Analysis Program) is a program that analyzes analog special services networks. SUBCAP (Subrate Configuration Analysis Program) examines networks designed for digital data services. The capabilities and application of each of the tools are discussed. Because the transmission equipment has the capabilities to support both types of services, and since shared applications are becoming increasingly popular, it is important to optimize the total network.     

Polarization Planning for Wireless Networks

Wireless Personal Communications - Polarization diversity enables frequency reuse in a telecommunication network. The most widely considered solution is to use two orthogonal polarizations on the...     

Efficient Memory Management for High-Speed ATM Systems

ATM technology placesstrict performance requirements on ATM systems, especially consideringthe scalability of the SDH/SONET physical layerto high speeds. Throughput preservation of the link speed throughprotocols to a higher layer application is a known problem inhigh-speed communication systems. The problem is being addressedwith design methodologies that offer high speed data paths, usingspecialized hardware, and increased processing power, commonlyin the form of embedded processors. In this paper, we presenta case study for a high-speed Queue Manager for ATM systems.The manager enables high-speed data transfer to/fromsystem memory and management of logical data structures (queues).Furthermore, it provides high-speed and importantly, scalabilityand re-usability, so that it can be used in a wide range of ATMsystems, such as workstation adapters, switches, routers, etc.In this work, we provide contributions in two directions. Wedescribe an approach to develop a high-speed, scalable and re-usablememory manager for ATM systems, and then we provide an architectureand implementations in harware as well as in software for embeddedsystems. The results indicate the cost/performancetrade-off's and system scalability and thus, enable designersto choose the implementation that meets their target system requirementswell.     

Energy-Efficient Route Selection Strategies for Wireless Sensor Networks

Wireless Sensor Networks (WSNs) facilitate monitoring and controlling of physical environments from remote locations with the best possible accuracy. Sensor networks are wireless networks consisting of groups of small, inexpensive nodes, which collect and disseminate critical data. Also, sensor nodes have various energy and computational constraints due to their inexpensive nature and ad hoc method of deployment. Considerable research has been focused on overcoming these deficiencies through low-energy consumption schemes. Among other factors, the route selection strategy may have an impact on the sensors lifetime, and following on the network lifetime. In this paper, we study various route selection strategies that aim at prolonging the lifetime of WSNs. Also, a new route selection scheme is proposed, that increases further the network lifetime. The performance of these schemes is analyzed through simulation.     

分形细胞神经网络用于联想记忆

本文提出了分形细胞神经网络，并成功地应用于联想记忆，从模拟结果看，分形细胞神经网络的联想记忆能力好于Ｂａｒａｍ提出的分形神经网络。     

Evidential Reasoning for Geographic Evaluation for Helicopter Route Planning

In order to plan operations where knowledge of significant elements is imprecise and uncertain, a means of characterizing the situation in terms of the various factors that may influence those operations must be provided. In this paper we discuss an approach to that characterization that uses evidential reasoning to handle the uncertainty, imprecision, and incompleteness typical of sources of real-world information and knowledge, to support planning routes for military helicopters. Evidential reasoning is a maturing collection of inference techniques for reasoning with uncertain information. Based on the Shafer-Dempster theory of evidence, evidential reasoning uses a non-Bayesian updating scheme to combine evidence provided by multiple diverse knowledge sources. Knowledge sources in an evidential reasoning system are not required to attribute their belief to a universe of discourse comprised solely of mutually exclusive, exhaustive, singleton events, as required by a classical probability approach. Rather, they may express levels of ignorance explicitly by allocating belief to disjunctions of propositions, thereby leading directly to an interval measure of belief; ignorance is expressed by the width of this interval. Evidential reasoning evolved from consideration of appropriate models for reasoning about information acquired from sensors, and therefore seems natural for drawing conclusions from sensor data and prestored maps regarding the degree to which a selected geographic area will support certain activities. Here, we discuss evidential reasoning and illustrate the utility of the technology for classifying geographic areas by describing our current map-and-sensor-based research in which we estimate the utility of land areas for concealing helicopter operations.