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2. Institute of Cyber-Systems and Control, Zhejiang University, Hangzhou 310007, China;
3. Key Laboratory of Machine Vision & Intelligent Information System, Chongqing University of Arts and Sciences, Chongqing 412060, China;
4. School of Information Engineering, Huzhou University, Huzhou 313000, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=zuwO3b7088wRLQJxpu9xkw==, pdfFileSize=3777231, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1242136499647488100, articleId=1242136496115884104, tenantId=1146029695717560320, journalId=1146031591421210625, language=CN, title=大数据驱动下智慧城市建设的若干思考, columnId=1242116830291099991, journalTitle=科技导报, columnName=学术聚焦, runingTitle=null, highlight=null, articleAbstract=在当前的智慧城市建设中,随着互联网、物联网、通信网及大规模智能化应用服务的深入发展,产生了海量、异构、多源的城市时空大数据。在大数据时代,智慧城市的建设值得人们更深层次的思考。如何应对这些大规模、复杂的城市数据,尤其是对数据的感知、采集、存储、管理、分析、挖掘、计算、可视化及高效的服务应用都面临着巨大挑战。本文主要从技术、立法、管理3个视角重点阐述了大数据对智慧城市发展驱动作用。在技术上从纵向和横向两个视角分析城市时空大数据的特征及应用;从数据资产的角度强调了立法在智慧城市中的作用;从政策管理、奖惩与市场机制等方面分析了管理在智慧城市建设中的重要性;从综合视角思考大数据驱动下智慧城市建设中的若干问题。, authors=马新强1,2,3 , 刘勇2 , 范婧2 , 黄羿1,3 , 吴茂念4 , 张明义1 , authorsList=马新强, 刘勇, 范婧, 黄羿, 吴茂念, 张明义, authorCompany=1. 贵州大学计算机科学与技术学院, 贵阳 550025;
2. 浙江大学智能系统与控制研究所, 杭州 310007;
3. 重庆文理学院机器视觉与智能信息系统重点实验室, 重庆 412060;
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科技导报
| 学术聚焦 2017, 35(21): 131-137
大数据驱动下智慧城市建设的若干思考
全屏
马新强1,2,3 , 刘勇2 , 范婧2 , 黄羿1,3 , 吴茂念4 , 张明义1
作者信息
1. 贵州大学计算机科学与技术学院, 贵阳 550025;
2. 浙江大学智能系统与控制研究所, 杭州 310007;
3. 重庆文理学院机器视觉与智能信息系统重点实验室, 重庆 412060;
4. 湖州师范学院信息工程学院, 湖州 313000
通讯作者:
刘勇(通信作者),教授,研究方向为机器学习、机器人,电子信箱:yongliu@iipc.zju.edu.cn
Big data-driven smart city:Some thoughts
Affiliations
出版时间: 2017-11-13
doi: 10.3981/j.issn.1000-7857.2017.21.016
文章导航
在当前的智慧城市建设中,随着互联网、物联网、通信网及大规模智能化应用服务的深入发展,产生了海量、异构、多源的城市时空大数据。在大数据时代,智慧城市的建设值得人们更深层次的思考。如何应对这些大规模、复杂的城市数据,尤其是对数据的感知、采集、存储、管理、分析、挖掘、计算、可视化及高效的服务应用都面临着巨大挑战。本文主要从技术、立法、管理3个视角重点阐述了大数据对智慧城市发展驱动作用。在技术上从纵向和横向两个视角分析城市时空大数据的特征及应用;从数据资产的角度强调了立法在智慧城市中的作用;从政策管理、奖惩与市场机制等方面分析了管理在智慧城市建设中的重要性;从综合视角思考大数据驱动下智慧城市建设中的若干问题。
智慧城市
/
大数据
/
城市计算
/
数据挖掘
/
可视化分析
In the construction of smart city, the depth development of Internet, Internet of things, communication networks and large-scale intelligent services will result in massive, heterogeneous, multi-source big spatio-temporal urban data. In the era of big data, we should think deeply about the construction of smart city. How to deal with these large-scale and complicated urban data is facing enormous challenges, including data collection, sensing, storage, management, mining, visualization and efficient services. In this paper we mainly discuss the driving effects of big data on smart city in the views of technology, legislation and management. We analyze the features and applications of big spatio-temporal urban data in two directions, point out the importance of legislation from the perspective of data assets, and summarize the management of smart city in terms of policy management, rewards and punishments, and market mechanisms. Finally, we put forward some thoughts on the construction of smart city driven by big data.
smart city
/
big data
/
urban computing
/
data mining
/
visual analysis
马新强, 刘勇, 范婧, 黄羿, 吴茂念, 张明义.
大数据驱动下智慧城市建设的若干思考.
科技导报,
2017
, 35
(21)
: 131
-137
.
DOI: 10.3981/j.issn.1000-7857.2017.21.016
MA Xinqiang, LIU Yong, FAN Jing, HUANG Yi, WU Maonian, ZHANG Mingyi.
Big data-driven smart city:Some thoughts[J].
Science & Technology Review ,
2017
, 35
(21)
: 131
-137
.
DOI: 10.3981/j.issn.1000-7857.2017.21.016
2017年第35卷第21期
PDF下载
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引用本文
BibTeX
文章信息
doi: 10.3981/j.issn.1000-7857.2017.21.016
接收时间:2017-03-23
首发时间:2017-11-16
出版时间:2017-11-13
收稿日期:2017-03-23
修回日期:2017-04-20
通讯作者:
刘勇(通信作者),教授,研究方向为机器学习、机器人,电子信箱:yongliu@iipc.zju.edu.cn
https://castjournals.cast.org.cn/joweb/kjdb/CN/10.3981/j.issn.1000-7857.2017.21.016
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2种不同金属材料的力学参数
科 Family 属数 Number of genus 种数 Number of species 占总种数比例 Percentage of total species (%) 属 Genus 种数 Number of species 占总种数比例 Percentage of total species (%) 鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78 小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39 多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39 红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87 小菇属 Mycena 11 5.26 光柄菇属 Pluteus 5 2.39 红菇属 Russula 17 8.13 栓菌属 Trametes 5 2.39
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