GIS在计量业务系统中的应用研究

<正>目前,我国计量业务系统的发展有了长足进步,但地理信息系统(GIS)技术在计量业务系统中的应用还不是很成熟。将GIS技术引入计量业务系统,可以以GIS的图形界面更直观地显示被检单位及被检单位计量器具的分布情况,方便集中安排外检,并可通过GIS技术进行车辆的智能调度。由此可见,GIS技术在计量业务系统中的应用具有广阔前景。一、GIS技术简介GIS(Geographical Information System)是地理信息系统的简称,是一种决策支持系统,它具有信息系统     

焦家金矿车辆GPS监控管理信息系统

利用全球定位系统(GPS,Global Positioning System)、地球信息系统(GIS,Geographic Information System)、全球移动通讯系统(GSM,Global System for Mobile communications)和Internet等技术,实施"车辆GPS监控管理信息系统",为车辆管理者提供车辆位置及其对其服务对象进行监控、远程控制、断油断电、紧急报警服务、偏离路线报警等功能。     

GPS/GIS技术在亳州烟草的应用和研究

目前GPS/GIS技术日益成熟,在车辆安全管理,车辆调度等方面应用广泛,安徽烟草早在08年开始着手全省GPS监控和送货线路优化等工作,目前已建立1个总的GPS监控中心,17个GIS和送货线路优化子系统,亳州作为安徽一个地级市,在安徽烟草总的平台下,通过完善系统功能,拓展相关应用,实践证明GPS/GIS在日常管理和应用中效果明显。     

LBS的关键技术及在车辆监控中的应用

LBS(Location Based Service),即基于位置的服务,是集合无线通信、GPS、GIS和Internet等技术开拓出来的极有前途的信息服务技术。分析LBS系统的体系结构,对LBS当前的定位、通讯、GIS等关键技术进行阐述,最后,介绍LBS在车辆监控信息管理上的应用。     

基于GIS/GPRS的双层数据物流平台

介绍基于GIS/GPRS等地理信息系统技术建立的双层数据物流平台在温州烟草销售过程中的应用。在传统的业务数据流基础上加入基于GIS地理信息系统的空间数据流,从而均衡的安排各区域工作量,有效控制物流成本。同时应用车辆监控系统控制物流车辆信息,实现物流的实时调配。通过建设双层数据物流平台,温州烟草完善了包括零售户信息的空间数据库,为进一步提高对零售户的管理和服务打下坚实的基础。     

对车辆管理信息系统的设计

车载GPS车辆管理信息系统是采用GPS、GSM/GPRS、GIS与计算机技术研究设计的对车辆进行导航、定位、调度、管理的计算机系统。车辆上的移动车载台可实时通过全球卫星定位系统获得自身的位置信息,定位信息通过无线通讯网络以短消息或GPRS形式传送到监控中心,并显示出来,而无线网络又可将监控中心的命令发送到车辆,由车载台执行。它是基于GIS平台,以功能强大的GIS软件--MapInfo为基础,利用高级编程语言Delphi进行开发,并在数据库系统SQL Server的支持下运行的。     

一种用于汽车电子导航的混合差值算法

介绍一种基于全球定位系统(GPS)和电子地图(GIS)的车辆路径诱导系统混合差值算法,实验结果显示,相比常用的Dijkstra's算法,混合差值算法在布线时间上减少60%。     

一种用于汽车电子导航的基因算法

介绍一种基于全球定位系统(GPS)和电子地图(GIS)的车辆路径诱导系统基因算法,实验结果显示,相比常用的Dijkstra’s算法,基因算法在布线时间上减少60%。     

一种用于汽车电子导航的禁忌搜寻法

介绍一种基于全球定位系统(GPS)和电子地图(GIS)的车辆路径诱导系统禁忌搜寻法,实验结果显示,相比常用的Dijkstra's算法,禁忌搜寻法在布线时间上减少27%。     

地理信息系统的发展与发展中的地理信息系统

针对目前对地理信息系统(GIS)的发展缺乏系统、规律性研究的问题,分析了地理信息系统产生和发展的社会前景、技术背景和学科背景;探讨了随着计算机通信网络技术的发展而引起的GIS体系结构和软件开发模式的变化,认为开放式GIS思想和组件式GIS更适合网络(网格)环境下数据服务和功能的服务分布式特点;提出GIS将向以网络服务(Web service)和网格服务(Grid service)为主要形式的开放式GIS方向发展,论述了基于网络服务的地理信息共享与数据互操作的基本架构及其特点,指出Grid service为实现信息资源共享和协同解决问题提供了新的机遇和技术途径,强调Web service和Grid service的核心都是服务,两者既相互联系又有区别.     

工程移民决策支持研究

工程移民指工程建设引起的非自愿的搬迁安置活动，工程移民决策包括规划决策和管理决策，这在国内外都是一个新课题，基于GIS的工程移民DSS是实施科学决策的有效手段，章对工程移民决策支持的理论、方法进行了探讨，并结合万家寨工程移民决策支持进行了试验。     

基于部分可观察马尔可夫决策过程的受控无线网络系统动态资源分配

研究了受控无线网络的动态资源分配。针对传统无线通信传输模型的局限性随着无线通信系统架构的发展日益凸显的问题,提出了一种引入反馈控制策略的受控无线网络模型。该模型结合部分可观察马尔可夫决策过程(POMDP),将用户接收功率与数据传输误码率作为反馈观测对象,对通信小区内基站天线开启数与用户接入数进行动态资源最优匹配。仿真结果表明,这种方法能够有效提升系统传输能效性与可靠性,降低传输误码率,改善系统资源动态匹配控制性能。     

Game Theory Based Decision Coordination Strategy of Agricultural Logistics Service Information System

Under the background of “Internet plus” rapid development, the agricultural logistics industry should apply information technology to every link of the agricultural product logistics industry chain. By making full use of the decision making module of the agricultural logistics information system, we can realize the full sharing of information and data resources, which makes the decision-making scheme of the agricultural logistics information system more optimized. In real economic society, the uncertainty and mismatch between the customer’s logistics service demand and the logistics service capability that the logistics service function provider can provide, that is, when the two information are asymmetric, how to use the third-party contract to coordinate the income and profit distribution of the two, to make the information system decision making more reasonable? This paper mainly studies the coordination scheme of agricultural logistics information system decision making under uncertain output and demand information by introducing the spot market. A joint coordination strategy based on revenue sharing and penalty feedback contracts proposes decentralized decision making based on game theory. Experiments show that the flexible ordering strategy proposed in this paper can reduce the logistics service supply chain’s uncertainty and significantly improve the logistics service supply chain’s overall income level through coordination contracts.     

Multi-Criteria Fuzzy-Based Decision Making Algorithm to Optimize the VHO Performance in Hetnets

Despite the seemingly exponential growth of mobile and wireless communication, this same technology aims to offer uninterrupted access to different wireless systems like Radio Communication, Bluetooth, and Wi-Fi to achieve better network connection which in turn gives the best quality of service (QoS). Many analysts have established many handover decision systems (HDS) to enable assured continuous mobility between various radio access technologies. Unbroken mobility is one of the most significant problems considered in wireless communication networks. Each application needs a distinct QoS, so the network choice may shift appropriately. To achieve this objective and to choose the finest networks, it is important to select a best decision making algorithm that chooses the most effective network for every application that the user requires, dependent on QoS measures. Therefore, the main goal of the proposed system is to provide an enhanced vertical handover (VHO) decision making program by using a Multi-Criteria Fuzzy-Based algorithm to choose the best network. Enhanced Multi-Criteria algorithms and a Fuzzy-Based algorithm is implemented successfully for optimal network selection and also to minimize the probability of false handover. Furthermore, a double packet buffer is utilized to decrease the packet loss by 1.5% and to reduce the number of handovers up to 50% compared to the existing systems. In addition, the network setup has an optimized mobility management system to supervise the movement of the mobile nodes.     

紫式决策分析架构模型及其实证研究

探讨工业工程在企业决策的定位,发展系统化的"紫式决策分析架构"和方法论,以辅助决策者有效地从问题定义与架构、目标和决策元素的分清、数据收集、信息整理、方案评估乃至决策支持的完整思维过程,建立决策问题的分析方式和解决方案,以找到最适合的优化决策,提供复杂管理问题数字化系统化之决策依据.具体说明紫式决策分析架构各阶段对应之步骤和方法,并以实证研究案例以检验效度.     

Embedding expert knowledge in a decision model: evaluating natural attenuation at TCE sites

This paper describes a generalized methodology that enables the translation of expert knowledge about any complex process involved in a remedial decision into easy-to-use decision tools. The methodology is applied to evaluate reductive dechlorination as a remedial possibility at sites contaminated with trichloroethene (TCE), building on an existing protocol/scoring system put forth by the US Air Force and the US EPA. An alternate scoring system is proposed, which has two major advantages, namely that it: (i) attributes relative weights to findings based on expert beliefs; and (ii) systematically includes negative weights for negative findings. The ability of the proposed scoring system to assess the bioattenuation potential of TCE is demonstrated using data from extensively studied sites.     

基于模糊神经网络的决策支持系统的应用研究

论述了模糊神经网络的概念及特点，在此基础上提出了基于模糊神经网络的决策支持模型，还介绍了其运行计算的过程与方法，并通过农机选型配套的决策支持实例验证模型，说明模型对复杂的决策问题具有简单方便及快速准确做出反应的优点。     

国内外农业大数据应用研究分析

针对农业领域数据规模大、数据结构复杂、空间数据挖掘能力不足等问题,研究了大数据开源技术在农业领域的数据分析体系中的应用。借鉴国内外学者在农业大数据的研究成果,基于农业数据时空属性的特征,结合农业数据的特点分析了Hadoop、Storm和Spark开源大数据挖掘技术,归纳性阐述了如何开发适合农业需求的大数据系统。最后,简要分析了农业大数据技术所面临的挑战和研究难题,指出需要加大力度进一步深入理论和应用研究,从而推动和实现基于数据的科学决策,为国家粮食提供安全保障。     

团队任务反思行为对决策绩效影响的实验研究

团队任务反思行为,是团队主动信息加工方式,影响着人们的判断与选择。因此,以团队任务反思行为理论为基础,提出了团队任务反思行为与决策绩效之间关系作用的研究假设。利用150名MBA学员展开了团队任务反思行为对决策质量、决策满意度和决策一致性影响效应的实验研究。研究结果表明,团队任务反思行为与决策质量有正"U"型相关关系,对决策满意度有显著正向预测效应,与决策一致性的正向相关关系显著。研究结果为决策群体利用团队任务反思提高决策绩效和团队效能有重要的实践意义。     

Enabling Smart Cities with Cognition Based Intelligent Route Decision in Vehicles Empowered with Deep Extreme Learning Machine

The fast-paced growth of artificial intelligence provides unparalleled opportunities to improve the efficiency of various industries, including the transportation sector. The worldwide transport departments face many obstacles following the implementation and integration of different vehicle features. One of these tasks is to ensure that vehicles are autonomous, intelligent and able to grow their repository of information. Machine learning has recently been implemented in wireless networks, as a major artificial intelligence branch, to solve historically challenging problems through a data-driven approach. In this article, we discuss recent progress of applying machine learning into vehicle networks for intelligent route decision and try to focus on this emerging field. Deep Extreme Learning Machine (DELM) framework is introduced in this article to be incorporated in vehicles so they can take human-like assessments. The present GPS compatibility issues make it difficult for vehicles to take real-time decisions under certain conditions. It leads to the concept of vehicle controller making self-decisions. The proposed DELM based system for self-intelligent vehicle decision makes use of the cognitive memory to store route observations. This overcomes inadequacy of the current in-vehicle route-finding technology and its support. All the relevant route-related information for the ride will be provided to the user based on its availability. Using the DELM method, a high degree of precision in smart decision taking with a minimal error rate is obtained. During investigation, it has been observed that proposed framework has the highest accuracy rate with 70% of training (1435 samples) and 30% of validation (612 samples). Simulation results validate the intelligent prediction of the proposed method with 98.88%, 98.2% accuracy during training and validation respectively.