热带地理 ›› 2018, Vol. 38 ›› Issue (6): 751-758.doi: 10.13284/j.cnki.rddl.003087
廖伟华a,聂 鑫b
出版日期:
2018-11-30
发布日期:
2018-11-30
通讯作者:
聂鑫(1983—),男,教授,博士,研究方向为土地资源管理,(E-mail)toefl678@163.com。
作者简介:
廖伟华(1975—),男,湖南耒阳人,副教授,研究方向为城市计算,(E-mail)gisliaowh@163.com;
基金资助:
国家自然科学基金项目(71403063、71763001);广西重点研发计划项目(桂科AB18126007)
LIAO Weihuaa, NIE Xinb
Online:
2018-11-30
Published:
2018-11-30
摘要:
同位模式表示不同类型的实体在空间邻域内共同频繁出现的规律,是城市实体空间关联的主要表达形式,但不能挖掘出指定实体的空间关联,需要寻找新的计算方法。在城市计算的视角下,通过引入粗糙集研究城市空间关联问题发现:1)该方法能把复杂的地理空间关联问题转换成信息决策问题,在信息决策表中计算城市实体之间的空间关联等拓扑关系,计算过程和结果可以挖掘城市行业之间的空间集聚和关联问题。2)通过属性约简得到属性核可以把高维空间数据降维,找到影响空间关联的重要因子。3)该方法拓宽了城市计算的理论方法体系和粗糙集方法的行业应用。最后,通过Python爬取南宁市城市服务业数据,进行方法的验证,计算结果与成熟的Apriori算法结果,以及南宁市服务业空间关联实际情况基本一致,证明了粗糙空间关联方法的可行性和正确性。
廖伟华,聂鑫. 城市计算视角下的空间粗糙关联规则方法研究[J]. 热带地理, 2018, 38(6): 751-758.
LIAO Weihua, NIE Xin. Spatial Rough Association Rules Method from the Perspective of Urban Computing[J]. TROPICAL GEOGRAPHY, 2018, 38(6): 751-758.
Bao J, He T, Ruan S and Li Y H. 2017.Planning Bike Lanes based on Sharing-Bikes’ Trajectories//In: ACM SIGKDD.International Conference on Knowledge Discovery and Data Mining.Halifax, NS: Canada ACM, 1377-1386.陈新保,朱建军,陈建群.2011.“多元”关联模式的时空数据挖掘.中南大学学报(自然科学版),42(1):106-114.[Chen Xinbao, Zhu Jianjun and Chen Jianqun. 2011. Mining multivariate association patterns from spatiotemporal data. Journal of Central South University (Science and Technology), 42(1):106-114.]傅伯杰.2014.地理学综合研究的途径与方法:格局与过程耦合.地理学报,69(8):1052-1059.[Fu Bojie. 2014. The integrated studies of geography: Coupling of patterns and processes. Acta Geographica Sinica, 69(8): 1052-1059. ]Hahsler M, Chelluboina S Hornik K and Buchta C.2011.The arules R-Package Ecosystem: Analyzing Interesting Patterns from Large Transaction Data Sets.Journal of Machine Learning Research, 12 (12): 2021-2025.Hitzler P and Janowicz K.2013.Linked Data, Big Data, and the 4th Paradigm.Semantic Web,4(3): 233-235. Ho V H, Compton P, Benatallah B and Vayssiere Julien.2009.An Incremental Knowledge Acquisition Method for Improving Duplicate Invoices Detection.Shanghai, China, 25th IEEE International Conference on Data Engineering.Iwata S.2012.Big Data Era.Journal of Information Processing & Management, 55(8): 543-551.Li S N, Dragicevic S, Castro F A, Sester M, Winter S, Coltekin A, Pettit C, Jiang B, Haworth J, Stein A and Cheng T. 2016.Geospatial big data handling theory and methods: A review and research challenges.Journalof Photogrammetry & Remote Sensing, 115: 119-133.Liao S H and Chang H K.2016.A rough set-based association rule approach for a recommendation system for online consumers.Information Processing & Management, 52 (6): 1142-1160.Liao S H, Chang W J and Lee C C.2008.Mining marketing maps for business alliances.Expert Systems with Applications, 35(3): 1338- 1350.李德仁.2016.展望大数据时代的地球空间信息学.测绘学报,45(4):379-384.[ Li Deren.2016. Towards Geo-spatial Information Science in Big Data Era.Acta Geodaetica et Cartographica Sinica, 45(4): 379- 384.]廖伟华,聂鑫.2017.基于大数据的城市服务业空间关联分析.地理科学,37(9):1310-1317.[Liao Weihua and Nie Xin. 2017.Spatial Association Analysis for Urban Service Based on Big Data. Scientia Geographica Sinica, 37(9): 1310-1317.]卢俊文,袁奇峰,黄哲,李志刚.2018.广州租赁住房的空间分布格局及其成因.热带地理,38(3):384-393.[Lu Junwen, Yuan Qifeng, Huang Zhe and Li Zhigang.2018.Spatial Pattern and Causes of Rental Housing in Guangzhou.Tropical Geography, 38(3): 384-393.]Merdun H and Ozturk Y. 2005. Introduction to arules-a computational environment for mining association rules and frequent item sets. Journal of Statistical Software, 14(15): 1-25.马荣华,马晓冬,蒲英霞.2005.从GIS数据库中挖掘空间关联规则研究.遥感学报,9(6):733-741.[Ma Ronghua, Ma Xiaodong and Pu Yingxia. 2005. Spatial Association Rule Mining from GIS Database. Journal of Remoting Sensing, 9(6): 733-741.]Naimi A I and Westreich D J.2013.Big Data: A Revolution That Will Transform How We Live, Work, and Think.Mathematics & Computer Education, 47 (17): 181-183.Ni L Q, Gao S S, Feng P C and Gai S S.2013.Rough Sets Probabilistic Data Association Algorithm and its Application in Multi-target Tracking.Defence Technology, 9(4): 208-216.Pang L X, Chawla S, Liu W and Zheng Y.2013.On detection of emerging anomalous traffic patterns using GPS data.Data & Knowledge Engineering, 87 (9): 357-373.Pawlak Z.1982.Rough sets.International Journal of Computer and Information Sciences,11(8): 341-356.Prado R P, Galan S G, Exposito J E M and Delgado A J Y.2011.Knowledge Acquisition in Fuzzy-Rule-Based Systems With Particle-Swarm Optimization.IEEE Transactions on Fuzzy Systems, 18 (6): 1083- 1097.Steiger E, Ellersiek T and Zipf A.2014.Explorative public transport flow analysis from uncertain social media data.Dallas, TX, United states: Geocrowd 14 Proceedings of the ACM Sig spatial International Workshop on Crowd sourced and Volunteered Geographic Information, 1-7.Steiger E, Westerholt R, Resch B and Zipf A.2015.Twitter as an indicator for whereabouts of people? Correlating Twitter with UK census data.Computers Environment & Urban Systems, 54: 255-265.Susan A.2017.Beyond prediction: Using big data for policy problems.Science, 355 (6324): 483-485.王国胤,姚一豫,于洪.2009.粗糙集理论与应用研究综述.计算机学报,32(7):1229-1246.[Wang Guoyin, Yao Yiyu and Yu Hong. 2009. A Survey on Rough Set Theory and Applications. Chinese Journal of Computers, 32(7): 1229-1246. ] 吴康敏,张虹鸥,王洋,叶玉瑶,金利霞,吴旗韬.2018.广州市零售业态空间分异特征与机制.热带地理,38(2):196-207.[Wu Kangmin, Zhang Hong’ou, Wang Yang, Ye Yuyao, Jin Lixia and Wu Qitao.2018.Spatial Differentiation and Formation Mechanism of Retail Industry in Guangzhou.Tropical Geography, 38(2): 196-207.]吴志峰,柴彦威,党安荣,龚建华,高松,乐阳,李栋,柳林,刘行健,刘瑜,龙瀛,陆锋,秦承志,王慧,王鹏,王伟,甄峰.2015.地理学碰上“大数据”:热反应与冷思考.地理研究,34(12):2207- 2221.[Wu Zhifeng, Chai Yanwei, Dang Anrong, Gong Jianhua, Gao Song, Yue Yang, Li Dong, Liu Lin, Liu Xingjian, Liu Yu, Long Ying, Lu Feng, Qin Chengzhi, Wang Hui, Wang Peng, Wang Wei and Zhen Feng. 2015. Geography interact with big data: Dialogue and reflection. Geographical Research, 34(12): 2207-2221. ] 徐志华,杨强,申玉铭.2016.区域中心城市服务业发展综合评价及其影响因素.地域研究与开发,35(3):40-45.[Xu Zhihua, Yang Qiang and Shen Yuming. 2016. Development of Service Sectors in Regional Central Cities and Its Influence Factors. Areal Research and Development, 35(3): 40-45. ]郑宇.2015.城市计算概述.武汉大学学报(信息科学版),40(1):1-13.[Zheng Yu. 2015. Introduction to urban computing. Geomatics and Information Science of Wuhan University, 40(1): 1-13.] |
[1] | 曹小曙,洪浩霖,梁斐雯. 高铁对中国城市群生产性服务业集聚的影响[J]. 热带地理, 2019, 39(3): 440-449. |
[2] | 王少剑,刘志涛,张婷婷,魏嘉仪,黄孚中. 服务业与多维城镇化的耦合协调研究 ——以广州市为例[J]. 热带地理, 2019, 39(3): 450-460. |
[3] | 钟 韵,吴 蒙. 区域合作背景下服务业发展的收敛性研究——以大珠三角金融业为例[J]. 热带地理, 2015, 35(2): 147-153. |
[4] | 杨 帆,叶嘉安. 中国生产性服务业发展与空间分布[J]. 热带地理, 2013, 33(2): 178-186. |
[5] | 钟 韵,刘 微. 现代服务业集聚区经济特性及其启示[J]. 热带地理, 2012, 32(5): 515-520. |
[6] | 张旺, 申玉铭, 周跃云. 长株潭城市群生产性服务业集聚的空间特征[J]. 热带地理, 2011, 31(4): 422-427,438. |
[7] | 钟韵. 广州市生产性服务业规模体系与空间布局研究——总部经济浪潮中的思考[J]. 热带地理, 2009, 29(6): 544-549. |
[8] | 林琳, 肖玲, 陈淳. 广州市汽车服务业布局实证研究[J]. 热带地理, 2009, 29(6): 550-554. |
[9] | 钟韵, 闫小培. 建国以来广州生产性服务业成长特征研究[J]. 热带地理, 2007, 27(4): 348-353. |
[10] | 王淑婧, 陈忠暖, 王开泳. 珠江三角洲与长江三角洲城市服务业竞争力比较分析[J]. 热带地理, 2005, 25(1): 54-58. |
[11] | 张润朋, 刘蓉. 新经济条件下我国生产性服务业的发展[J]. 热带地理, 2002, 22(4): 315-319. |
[12] | 谭丽燕. 南宁市旅游商品开发研究[J]. 热带地理, 2002, 22(1): 71-75. |
[13] | 龙国英, 易晓峰, 黄瑛. 汕头市的城市性质和功能定位[J]. 热带地理, 2001, 21(4): 295-300. |
[14] | 阎小培. 广州信息服务业增长的地域类型分析[J]. 热带地理, 1999, 19(1): 18-22. |
[15] | 阎小培, 姚一民. 中心城市信息来源、加工和扩散研究──以《广州日报》为例[J]. 热带地理, 1996, 16(4): 362-371. |
|