[1]吴保宽.应用ANN与CA构建GIS模型的城市非正规商业行为分析[J].华侨大学学报(自然科学版),2017,38(4):497-502.[doi:10.11830/ISSN.1000-5013.201704010]
　WU Baokuan.Analysis of Urban Informal Business Behavior Based onGIS Model Constructed by ANN and CA[J].Journal of Huaqiao University(Natural Science),2017,38(4):497-502.[doi:10.11830/ISSN.1000-5013.201704010]
点击复制

应用ANN与CA构建GIS模型的城市非正规商业行为分析()
分享到：

《华侨大学学报（自然科学版）》[ISSN:1000-5013/CN:35-1079/N]

卷:
第38卷
期数:
2017年第4期
页码:
497-502
栏目:
出版日期:
2017-07-10

文章信息/Info

Title:
Analysis of Urban Informal Business Behavior Based onGIS Model Constructed by ANN and CA
文章编号:
1000-5013(2017)04-0497-06
作者:
吴保宽
华侨大学 建筑学院, 福建 厦门 361021
Author(s):
WU Baokuan
College of Architecture, Huaqiao University, Xiamen 361021, China
关键词:
城市非正规商业行为;  神经网络算法;  元细胞自动机;  地理信息系统;  环境因子
Keywords:
urban informal business behavior;  artificial neural networks;  cellular automation;  geographic information system;  environmental factors
分类号:
TU17
DOI:
10.11830/ISSN.1000-5013.201704010
文献标志码:
A
摘要:
基于神经网络算法(ANN)和元细胞自动机(CA),建构台湾逢甲夜市商圈的地理信息系统(GIS)模型,并对非正规摊贩商业行为进行数值模拟与实证分析.研究结果表明:非正规摊贩分布模拟结果为平均正确率84.1%,而目标模式的平均正确率可达94.2%;在环境因子影响性分析方面,街道位置类型是发生非正规摊贩最具影响性的环境因子,而背景建物宽度则是最不具影响性的环境因子;在环境因子相关性分析方面,街道位置类型因子是所有假设环境因子中最能吸引非正规摊贩聚集的正相关因子.
Abstract:
Based on the artificial neural network(ANN)algorithm and the cellular automation(CA), the geographic information system(GIS)model of the Fengjia night market in Taiwan was constructed, the commercial behavior of the informal street vendors was simulated. The results show that: the average simulation accuracy of the informal street vendor distribution is 84.1%, but the average simulation accuracy of target pattern is 94.2% high. In the environmental factor impact analysis, the street location type is the most influential environmental factor of the informal vendors. The background building width is the least influential environmental factor. In the environmental factor correlation analysis, the street position type factor is the positive correlation factor that is the most attractive environmental factor for attracting informal vendors.

参考文献/References:

[1] THAPA R B,MURAYAMA Y.Urban growth modeling of Kathmandu metropolitan region, Nepal[J].Computers Environment and Urban Systems,2011,35(1):25-34.
[2] SANT I,GARC A A M,MIRANDA D,et al.Cellular automata models for the simulation of real-world urban processes: A review and analysis[J].Landscape and Urban Planning,2010,96(2):108-122.
[3] BOLSTAD P.GIS Fundamentals: A first text on geographic information systems[M].3rd ed.White Bear Lake,Minn: Eider Press,2008:15-36.
[4] 胡永进.地理信息系统在城市规划中的应用[J].江苏城市规划,2010(5):32-37.
[5] BATTU M.Modelling urban development with geographical information systems and cellular automata[M].Boca Raton:CRC Press,2009:11-27.
[6] PIJANOWSKI B C,TAYYEBI A,DOUCETTE J,et al.A big data urban growth simulation at a national scale: Configuring the GIS and neural network based land transformation model to run in a high performance computing(HPC)environment[J].Environmental Modelling and Software,2014,51:250-268.
[7] GREKOUSIS G,MANETOS P,PHOTIS Y N.Modeling urban evolution using neural networks, fuzzy logic and GIS: The case of the Athens metropolitan area[J].Cities,2013,30(1):193-203.
[8] BASSE R M,OMRANI H,CHARIF O,et al.Land use changes modelling using advanced methods: Cellular automata and artificial neural networks. The spatial and explicit representation of land cover dynamics at the cross-border region scale[J].Applied Geography,2014,53:160-171.
[9] HAUPT S E,LAKSHMANAN V, MARZBAN C, et al.Environmental science models and artificial intelligence[C]//Artificial Intelligence Methods in the Environmental Sciences.Netherlands:Springer,2009:3-13.
[10] DUDA R O,HART P E,STORK D G.Pattern classification[M].2nd ed.New York:Wiley,2001:25-61.
[11] BISHOP C M.Neural networks for pattern recognition[M].New York:Oxford University,1995:76-93.
[12] YASSEMI S,DRAGI(-overC)EVIC(-overC),SCHMIDT M.Design and implementation of an integrated GIS-based cellular automata model to characterize forest fire behaviour[J].Ecological Modelling,2008,210(1/2):71-84.
[13] ZHANG G P.An investigation of neural networks for linear time-series forecasting[J].Computers and Operations Research,2001,28(12):1183-1202.
[14] HSIEH A T,CHANG J.Shopping and tourist night markets in Taiwan[J].Tourism Management,2006,27(1):138-145.
[15] YATMO Y A.Perception of street vendors as out of place urban elements at day time and night time[J].Journal of Environmental Psychology,2009,29(4):467-476.
[16] MARZBAN C.Basic statistics and basic AI: Neural networks[C]//Artificial Itelligence Methods in the Environmental Sciences.Netherlands:Springer,2009:15-47.

备注/Memo

备注/Memo:
收稿日期: 2016-10-17
通信作者: 吴保宽(1976-),男,讲师,博士,主要从事人工智能技术应用于城乡建筑设计与规划的研究.E-mail:py1006@hqu.edu.cn.
基金项目: 国家自然科学基金资助项目(41401224); 福建省自然科学基金资助项目(2016J01238)
更新日期/Last Update: 2017-07-20