Multi-source macro data process based on the idea of sample=overall in big data

an applicability study on influence factors to smart city

Li Xiong, Shan Xue, Shufen Yang, Changling Han

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contribution

1 Citation (Scopus)

Abstract

For the current applicable discussions on the idea of sample=overall in big data processing, this paper selects macro data from multi-source including influence factors of smart city from 17 districts and counties of Shanghai as an overall sample, and standardizes the data. Then, another sample is created from output of Principal Components Analysis (PCA). By comparing the two types of samples in the study of cluster analysis, three conclusions are founded. Firstly, standardization of data processing can serve to strengthen the role of dynamic networks and dynamic system stability. Secondly, factors beyond the principal components also have information carrying capacity and the impact capacity to complex dynamic systems. Thirdly, the amount of information carried by the non-principal components in practical application is much larger than the amount in measurement. Thus, we prove the idea of sample=overall in big data is very suitable for multi-source macroeconomic data processing compared to a selected sample.

Original languageEnglish
Title of host publication2015 International Conference on Logistics, Informatics and Service Science, LISS 2015
Subtitle of host publicationProceeding
EditorsZhenji Zhang, Runtong Zhang, Vicenc Fernandez, Shifeng Liu
Place of PublicationPiscataway, NJ
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9781479918904
ISBN (Print)9781479918904
DOIs
Publication statusPublished - 2015
Externally publishedYes
EventInternational Conference on Logistics, Informatics and Service Science, LISS 2015 - Barcelona, Spain
Duration: 27 Jul 201529 Jul 2015

Conference

ConferenceInternational Conference on Logistics, Informatics and Service Science, LISS 2015
CountrySpain
CityBarcelona
Period27/07/1529/07/15

Keywords

  • big data
  • cluster
  • multi-source
  • PCA
  • sample selection
  • smart city

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