GIS在城市固体废物管理中应用及与专业模型的耦合

GIS在城市固体废物管理领域的应用可从基本数据采集、数据与信息管理、基本空间分析、GIS与专业模型结合、空间决策支持系统建立五个层次进行.当前GIS的研究热点之一是GIS与专业模型结合,其结合方式包括基于数据传输的松散式结合、基于共同用户界面的表面无缝结合、内嵌式结合等,基于组件开发技术实现两者结合的方法最具有前景,符合当前GIS发展的趋势.实践证明,GIS与城市固体废物管理专业模型结合具有明显的优势.     

应用空间决策支持系统进行城市人口预测初探

空间决策支持系统（Spatial Decision Support System,SDSS)是以地理信息系统（Geographical Information System,GIS)为基础，以模型库为核心，具有信息分析与存贮、信息评价与预测及信息决策与管理的面向对象、面向空间信息和面向用户的决策系统。文章对应用空间决策支持系统进行城市人口预测进行了探讨，提出了基本的系统总体构想。     

多媒体教学软件开发，高性能计算软件开发和留学人员服务以及联合办学，远程教育

项目所有人：汤勤；所在国：美国；专业：软件开发，GIS；学历：博士 项目简介：GGITS是一个集GPS，GIS，无线通讯，英特网和智能交通等技术为一体的综合高科技系统，主要用于动态监测和发布城市交通状况，提供紧急情况处理（故障、车祸、打劫），交通状况分析和预测，动态最佳路经选择，以及交通规划决策支持。     

城市重大污染事件监测报警应急系统集成平台

城市重大污染事件监测报警应急系统集成平台基于Web GIS，系统以城市电子地图为背景，组合城市现有的小网格大气环境、污染监测网资源，建立重大污染突发事件车载移动现场监测系统，应急指挥调度系统，实现对重大污染事件现场污染扩散三维动态监测预测。集成平台是一个多部门处理突发重大污染事件的协同工作平台。     

基于GIS的煤矿企业风险预测预警系统设计

为及时掌握煤矿风险信息并对风险进行有效预测预警,设计了一种基于GIS的煤矿企业风险预测预警系统。该系统利用GIS信息采集平台对危险源信息进行有效的采集处理;利用风险预警模型对采集的信息进行数据挖掘分析、算法运算分析等综合预测分析,并得出风险预警结论;利用GIS分析展现平台对预警结果进行综合可视化预警与展现,为矿井安全生产调度提供辅助决策支持。该系统可实现煤矿企业风险治理的精准管控。     

聚类算法分析及在GIS中心选址中的仿真研究

通过对聚类算法初始点选择策略的分析和比较,经典k-means算法在GIS海量数据处理上的效率问题,提出了随机采样的k-means算法来进行坐标聚类;并将随机采样k-means算法应用于GIS中心选址,充分利用GIS数据分析和处理能力,以城市间的欧几里得距离为相似条件,采用最大最小原则选取初始点进行聚类,从而缓解局部最优解产生的概率;选取中心城市作为目标对象,从而提高商业决策的充分性和可靠性;经仿真结果验证了所提出的随机取样k-means算法的有效性和正确率。     

基于GIS交通源分布数据库技术的研究

交通源分布是城市交通管理和规划的重点对象和考虑因素。本文探讨通过对现有的城市机动车辆数据和人口数据进行交通分区处理，建立人口与车辆等交通源分布的数据库系统，生成交通源GIS分布数据，为城市交通管理者在做有关城市交通管理和规划方面提供决策数据。     

湛江城市数字交通管理信息系统的研究

随着“数字地球”概念的提出，“数字城市”已经成为GIS领域中的一个热门话题。数字交通管理信息系统选用mpinfo为地理信息系统平台，利用先进的计算机网络技术、地理信息系统技术GIS，在建立湛江市城市交通信息库的基础上，紧密结合数字交通管理的业务流程。实现对城市交通的科学规划、管理和决策。     

GIS在历史文化资源保护中的应用研究

基于GIS进行历史文化资源的保护就是利用GIS对历史文化资源及其配套设施进行查询、检索和显示．采用GIS的分析功能对历史文化资源的保护进行监控和规划，并通过预测模型对历史文化资源的保护提供决策支持，可应用于文化资源保护、城市发展规划、旅游资源开发、景观设计等领域。     

GIS技术在城市建设决策支持系统中的应用初探

文章介绍了以地理信息系统（Goeographical Information System,GIS)为基础的城市建设决策支持系统及总体设计框架，它是具有信息分析与存贮，信息评价与预见到信息决策与生理的面向对象、空间和用户的决策系统，它提供了快速、多后次、高质量的信息服务和辅助决策。     

Continuous-discrete simulation-based decision making framework for solid waste management and recycling programs

Solid waste produced as a by-product of our daily activities poses a major threat to societies as populations grow and economic development advances. Consequently, the effective management of solid waste has become a matter of critical importance for communities. However, solid waste management systems are inherently large-scale, diverse, and subject to many uncertainties, and must serve numerous stakeholders with divergent objectives. In this study, we propose a simulation-based decision-making and optimization framework for the analysis and development of effective solid waste management and recycling programs. The proposed solution includes a database and two main modules: an assessment module and a resource allocation optimization module. The assessment module identifies the sources of uncertainties in the system, which are then parameterized and incorporated into the resource allocation optimization module. The resource allocation optimization module involves a novel discrete–continuous model of the system under consideration, in which the continuous nature of decision variables is maintained while inherently discrete processing and transfer operations are accurately captured. The model operates with respect to the waste types and characteristics, costs, environmental impacts, types, location and capacities of processing facilities, and their technological capabilities. Then, an optimization mechanism embedded in the resource allocation optimization module solves the multi-criteria problem of the allocation of limited resources by simultaneously optimizing all relevant decision variables, evaluating performance in real-time via the model. Here, the optimum solution is considered as the combination of parameters that will lead to the highest recycling rate with minimum cost. The proposed framework has been successfully demonstrated for the Miami-Dade County Solid Waste Management System in the State of Florida.     

基于多模型拟合的西安市生活垃圾量预测

大城市生活垃圾预测是政府环卫部门安全评价、规划和决策的基础。以西北最大城市西安为例,在分析现状基础上得出目前影响西安市生活垃圾产量的三个显著的驱动因子：西安市辖区建成区土地面积、城镇居民人均可支配收入和市区户籍人口。先建立GM（1,1）灰色预测模型和最小二乘法多项式拟合人均可支配收入增长模型,对三个影响因素指标分别进行预测;后建立多元线性回归模型,结合前期三个指标预测值,预测2011-2020年西安市生活垃圾产生量。显著性F检验表明多模型拟合预测合理,预测结果有意义。     

基于GIS的长江三峡工程诱发地震预测信息管理与辅助决策系统

从系统需求分析出发,介绍了长江三峡工程水库诱发地震预测信息管理与辅助决策系统以地理信息系统(GIS)为基础平台的可视化设计思想及其相应结构体系,研制并开发了基础信息综合管理与分析模块、水库诱发地震概率预测与评估模块、按学科的水库诱发地震预测模块以及抗震救灾指挥辅助决策模块等多个主模块以及系统帮助模块等辅模块,并对各主要模块的功能分别进行了论述。     

Site selection in waste management by the VIKOR method using linguistic assessment

Site selection is an important issue in municipal solid waste (MSW) management. Selection of the appropriate solid waste site is an extensive evaluation process that requires consideration of multiple alternative solutions and evaluation criteria. In reality, it is easier for decision makers to express their judgments on the alternatives by using linguistic terms, and there usually exists uncertain and incomplete assessment information. Moreover, decision makers may have different risk attitudes in the siting process because of their different backgrounds and personalities. Therefore, an attitudinal-based interval 2-tuple linguistic VIKOR (ITL-VIKOR) method is proposed in this paper to select the best disposal site for MSW. The feasibility and practicability of the proposed method are further demonstrated through an example of refuse-derived fuel (RDF) combustion plant location. Results show that the new approach is more suitable and effective to handle the MSW site selection problems by considering the decision maker's attitudinal character and incorporating the uncertain and incomplete assessment information.     

空间信息支持下的江西定南稀土矿区泥石流危险性评价

江西省定南县是我国离子型稀土矿的主要产区。在稀土开采的同时,产生了大量水土流失,诱发的多处泥石流淹没林地和耕地。运用QuickBird高分辨率遥感信息与3D可视化技术相结合对定南矿区开采面、固体废弃物及其造成的泥石流进行解译,根据泥石流分布特点选取危险性评价因子,建立了评价模型,依据预测结果划分了泥石流的危险性空间分布。预测结果得到遥感影像和野外实际调查的检验,模型在赣南离子型稀土矿区有一定的推广意义。     

数据驱动的城市固废焚烧过程烟气含氧量预测控制

烟气含氧量的精准控制对城市固废焚烧处理厂的稳定高效运行具有重要意义.然而,由于固废焚烧过程固有的非线性和不确定性,难以实现烟气含氧量的有效控制.为此,文中提出一种数据驱动的城市固废焚烧过程烟气含氧量预测控制方法.首先,设计了一种基于自组织长短期记忆(SOLSTM)网络的预测模型,结合神经元活跃度与显著性动态调整隐含层结构,提高了烟气含氧量的预测精度.其次,为了保证优化效率,利用梯度下降法求解控制律.此外,基于李雅普诺夫理论分析了所提方法的稳定性,确保控制器在实际应用过程中的可靠性.最后,基于实际工业数据对所提出的控制方法进行了验证,结果表明,提出的数据驱动预测控制方法能实现对城市固废焚烧过程烟气含氧量的稳定高效控制.     

Theoretical model and implementation of a real time intelligent bin status monitoring system using rule based decision algorithms

Due to the rising trend of urbanization along with overconsumption of non-recyclable resources, the volume of municipal solid waste is increasing every day. An efficient, cost effective and environment friendly solution for real time bin status monitoring, collection and transportation of municipal solid waste is still a major challenge to the local municipal authorities. This research proposes a novel model, architecture and intelligent sensing algorithm for real time solid waste bin monitoring system that would contribute to the solid waste collection optimization. The monitoring application is based on decision algorithms for sensing solid waste data in a wireless sensor network. The system is built on a three level architecture like smart bin, gateway and control station. The elementary concept is that, smart bins collect their status when any changes occur and transmit the status data to a server via an intermediate coordinator. A set of applications in server presents the updated bin status on real time. The field test performances show that the system can efficiently monitor real time bin status that makes it feasible to decide, which bin should collect and which should not. Thus the proposed system has achieved its goal to provide real time bin status information to the solid waste management operator. Later, this information can be used for collection route optimization to reduce collection costs and carbon emissions which in turn contribute to build green society.     

An inexact fuzzy-queue programming model for environmental systems planning

In this study, an inexact fuzzy-queue programming (IFQP) model is developed for municipal solid waste (MSW) management under uncertainty, where fuzzy queue (FQ) model is introduced into the interval-fuzzy linear programming (IFLP) framework. The proposed IFQP model can not only handle uncertainties that are presented in terms of fuzzy sets and discrete intervals, but also reflect the influence of FQ in decision-making problems. Moreover, it can help quantify the satisfaction degrees of the system cost and constraints under uncertainty. It improves upon the existing optimization model with advantages in data availability, uncertainty reflection and result analysis. In its solution process, the model is transformed into two deterministic submodels based on an interactive algorithm. Interval solutions which are stable in the decision space can be obtained by solving the two submodels sequentially. The developed model is applied to a case of long-term planning of MSW management systems to demonstrate its applicability. It can effectively reflect dynamic, interactive, and uncertain characteristics of municipal waste management systems. The decision variable solutions provide optimal schemes for waste flow allocation corresponding to lower and upper bounds of system cost. The results indicate that reasonable solutions have been generated. They are helpful for supporting: (i) decision making or justification of waste-allocation patterns of MSW management system, and (ii) in-depth analysis of tradeoffs among system cost, satisfaction degree, and environmental constraint under uncertainty.     

Assessing a fuzzy model and HSPF to supplement rainfall data for nonpoint source water quality in the Feitsui reservoir watershed

The objective of this study was to improve the use of a fuzzy model to supplement rainfall data when the watershed's meteorological station is either far away or suffers a loss of rainfall data. The fuzzy model can also supplement rainfall data when the station is nearby. The accuracy of rainfall data in the EPA's (Environmental Protection Agency) BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. This study also assessed the improvement in stream flow prediction with the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS, using the hourly precipitation estimates for the Feitsui reservoir watershed. This study demonstrates that using a fuzzy model to supplement rainfall data has the potential to improve stream flow predictions, thus aiding water quality assessment in the nonpoint water quality assessment decision tool.