[1]丘健妮[],陈少沛[]. 城市慢行交通网络数据建模研究[J].计算机技术与发展,2014,24(12):48-52.
 QIU Jian-ni[],CHEN Shao-pei[]. Study on Urban Non-motorized Transportation Network Data Modeling[J].,2014,24(12):48-52.
点击复制

 城市慢行交通网络数据建模研究()
分享到:

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
24
期数:
2014年12期
页码:
48-52
栏目:
智能、算法、系统工程
出版日期:
2014-12-10

文章信息/Info

Title:
 Study on Urban Non-motorized Transportation Network Data Modeling
文章编号:
1673-629X(2014)12-0048-05
作者:
 丘健妮[1] 陈少沛[2]
1. 广州地理研究所;2.广东财经大学 公共管理学院
Author(s):
 QIU Jian-ni[1] CHEN Shao-pei[2]
关键词:
 城市慢行交通统一建模语言地理标识语言数据建模
Keywords:
 urban non-motorized transportationUnified Modeling Language(UML)Geography Markup Language(GML)data mod-eling
分类号:
TP31
文献标志码:
A
摘要:
 城市慢行交通系统是现代城市交通系统的重要组成部分,随着多模式城市交通发展,建立便捷和高效的城市慢行交通网络系统成为现代城市解决交通问题和提升交通运行效率的关键措施。基于此,文中应用统一建模语言( UML)和地理标识语言( GML)建立城市慢行交通网络数据模型,提出一种统一的和一致性的交通地理要素定义和性质描述方法,并阐述基于GML的城市慢行交通网络的地理要素和关系表达。研究成果促进了城市交通地理数据的组织、表达、集成、共享和操作,对建立高效的城市慢行交通网络系统具有重要的理论价值。
Abstract:
 Urban non-motorized transportation system is the important component of modern urban transportation system. With the devel-opment of multi-modal transportation,it is the key measure to build a convenient and efficient urban non-motorized transportation system for modern cities to deal with traffic problem and improve traffic running efficiencies. Therefore, apply Unified Modeling Language ( UML) and Geography Markup Language ( GML) to construct an urban non-motorized transportation network data model,and present an unified and consistent transportation geography features’ definitions and the methods of their properties representation. As a result,de-scribe the representation of the geography elements and their relationships in urban non-motorized transportation network based on GML. The result in this paper promotes the organization,representation,integration,sharing and operation of urban transportation data,and has theoretic value for a high efficient transportation network system.

相似文献/References:

[1]张志宏,吴庆波,邵立松,等.基于飞腾平台TOE协议栈的设计与实现[J].计算机技术与发展,2014,24(07):1.
 ZHANG Zhi-hong,WU Qing-bo,SHAO Li-song,et al. Design and Implementation of TCP/IP Offload Engine Protocol Stack Based on FT Platform[J].,2014,24(12):1.
[2]梁文快,李毅. 改进的基因表达算法对航班优化排序问题研究[J].计算机技术与发展,2014,24(07):5.
 LIANG Wen-kuai,LI Yi. Research on Optimization of Flight Scheduling Problem Based on Improved Gene Expression Algorithm[J].,2014,24(12):5.
[3]黄静,王枫,谢志新,等. EAST文档管理系统的设计与实现[J].计算机技术与发展,2014,24(07):13.
 HUANG Jing,WANG Feng,XIE Zhi-xin,et al. Design and Implementation of EAST Document Management System[J].,2014,24(12):13.
[4]侯善江[],张代远[][][]. 基于样条权函数神经网络P2P流量识别方法[J].计算机技术与发展,2014,24(07):21.
 HOU Shan-jiang[],ZHANG Dai-yuan[][][]. P2P Traffic Identification Based on Spline Weight Function Neural Network[J].,2014,24(12):21.
[5]李璨,耿国华,李康,等. 一种基于三维模型的文物碎片线图生成方法[J].计算机技术与发展,2014,24(07):25.
 LI Can,GENG Guo-hua,LI Kang,et al. A Method of Obtaining Cultural Debris’ s Line Chart Based on Three-dimensional Model[J].,2014,24(12):25.
[6]翁鹤,皮德常. 混沌RBF神经网络异常检测算法[J].计算机技术与发展,2014,24(07):29.
 WENG He,PI De-chang. Chaotic RBF Neural Network Anomaly Detection Algorithm[J].,2014,24(12):29.
[7]刘茜[],荆晓远[],李文倩[],等. 基于流形学习的正交稀疏保留投影[J].计算机技术与发展,2014,24(07):34.
 LIU Qian[],JING Xiao-yuan[,LI Wen-qian[],et al. Orthogonal Sparsity Preserving Projections Based on Manifold Learning[J].,2014,24(12):34.
[8]尚福华,李想,巩淼. 基于模糊框架-产生式知识表示及推理研究[J].计算机技术与发展,2014,24(07):38.
 SHANG Fu-hua,LI Xiang,GONG Miao. Research on Knowledge Representation and Inference Based on Fuzzy Framework-production[J].,2014,24(12):38.
[9]叶偲,李良福,肖樟树. 一种去除运动目标重影的图像镶嵌方法研究[J].计算机技术与发展,2014,24(07):43.
 YE Si,LI Liang-fu,XIAO Zhang-shu. Research of an Image Mosaic Method for Removing Ghost of Moving Targets[J].,2014,24(12):43.
[10]余松平[][],蔡志平[],吴建进[],等. GSM-R信令监测选择录音系统设计与实现[J].计算机技术与发展,2014,24(07):47.
 YU Song-ping[][],CAI Zhi-ping[] WU Jian-jin[],GU Feng-zhi[]. Design and Implementation of an Optional Voice Recording System Based on GSM-R Signaling Monitoring[J].,2014,24(12):47.

更新日期/Last Update: 2015-04-15