Discovering the Association of Algae with Physicochemical Variables in Erhai Lake

LIU Chuanlu; WANG Shuliang; YUAN Hanning; GENG Jing

doi:10.1049/cje.2020.01.003

Volume 29 Issue 2

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LIU Chuanlu, WANG Shuliang, YUAN Hanning, et al. “Discovering the Association of Algae with Physicochemical Variables in Erhai Lake”. Chinese Journal of Electronics, vol. 29 no. 2. doi: 10.1049/cje.2020.01.003

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LIU Chuanlu, WANG Shuliang, YUAN Hanning, et al. “Discovering the Association of Algae with Physicochemical Variables in Erhai Lake”. Chinese Journal of Electronics, vol. 29 no. 2. doi: 10.1049/cje.2020.01.003

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Discovering the Association of Algae with Physicochemical Variables in Erhai Lake

doi: 10.1049/cje.2020.01.003

School of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China

Funds: This work is supported supported by National Key Research and Development Program of China (No.2016YFC0803000), Beijing Municipal Science and Technology Project (No.BJMSJY-170167), Open Fund of Key Laboratory for National Geographic Census and Monitoring, National Administration of Surveying Mapping and Geoformation(No.2017NGCMZD03).

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Corresponding author: WANG Shuliang (corresponding author) Ph.D., IEEE Senior Member, is a professor in Beijing Institute of Technology in China. His research interests include spatial data mining, and software engineering. (Email:slwang2011@bit.edu.cn)
Received Date: 2019-06-03
Rev Recd Date: 2019-06-25
Publish Date: 2020-03-10

Abstract

Abstract

Erhai Lake is the seventh largest freshwater lake in China where has been encountered with water pollution by the algae. One of important indicator of the water quality is the density of algae in the water, and the growth rate of algae is eutrophication. A novel method is proposed to discover the association of algae with physicochemical variables related to the algae growth in Erhai Lake, by integrating Maximal information coefficient(MIC) and association rules. To measure the correlation between variables, a new aspect on association rules with non-occurring domain is purposed, which decreases one item in antecedent. The correlation results present significantly in the density levels of algae, which is beneficial to control the level of physicochemical in the water for preventing the increasing number of algae.
- Erhai Lake,
- Algae,
- Maximal information coefficient(MIC),
- Association rules

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References(38)

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