Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)

Application of Association Rules Big Data Analysis in Building Safety Production Supervision System

Authors
Ganglong Fan, Hongsheng XuXu
Corresponding Author
Ganglong Fan
Available Online September 2016.
DOI
10.2991/meici-16.2016.204How to use a DOI?
Keywords
Big data; Safety production supervision; Association rule; Cloud platform; Pattern analysis
Abstract

This paper first discusses building of safety production supervision system in smart city by cloud platform and points out the existing problems. Then, this paper analyzes pattern of association rules data mining for big data background. The task of big data mining is to discover patterns hidden in the safety production supervision data, and its patterns are divided into two categories: descriptive model and predictive model. Finally, the paper presents application of association rules big data analysis in building safety production supervision system.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
Series
Advances in Intelligent Systems Research
Publication Date
September 2016
ISBN
10.2991/meici-16.2016.204
ISSN
1951-6851
DOI
10.2991/meici-16.2016.204How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Ganglong Fan
AU  - Hongsheng XuXu
PY  - 2016/09
DA  - 2016/09
TI  - Application of Association Rules Big Data Analysis in Building Safety Production Supervision System
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 984
EP  - 988
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.204
DO  - 10.2991/meici-16.2016.204
ID  - Fan2016/09
ER  -