Application of Data Mining Technology in Intelligent Environmental Protection Systems

DOI

10.2991/icaita-16.2016.6How to use a DOI?

Keywords

intelligent environmental protection; data mining techniques; association rules; flue gas desulfurization monitor

Abstract

Among the pollutants in the power industry emissions, sulfur dioxide so far has the most serious impact on the environment. In the desulfurization process, it is common to have data with complex correlations, high real-time, and huge amount. Data mining has become an important technique to deal with these data, and to facilitate better environmental protection and pollution control over the total emissions. The theme of this paper is to effectively analyze the correlation between data, via data mining technology and data association rules, to improve overall decision-making capabilities, and then to provide a reliable basis for intelligent environmental protection. In this paper, we propose parameters predictive model. We verify the proposed algorithms using actual monitoring data of desulfurization processes, and demonstrate that the application of the models has achieved good performance in desulfurization monitoring.

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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TY  - CONF
AU  - Guikang Gao
AU  - Mingbo Xiao
AU  - Zhen Wang
PY  - 2016/01
DA  - 2016/01
TI  - Application of Data Mining Technology in Intelligent Environmental Protection Systems
BT  - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications
PB  - Atlantis Press
SP  - 23
EP  - 26
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaita-16.2016.6
DO  - 10.2991/icaita-16.2016.6
ID  - Gao2016/01
ER  -