Issue |
ITM Web Conf.
Volume 11, 2017
2017 International Conference on Information Science and Technology (IST 2017)
|
|
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Article Number | 01008 | |
Number of page(s) | 8 | |
Section | Session I: Computational Intelligence | |
DOI | https://doi.org/10.1051/itmconf/20171101008 | |
Published online | 23 May 2017 |
Forecast Model of Urban Stagnant Water Based on Logistic Regression
1 Faculty of Information Technology, Beijing University of Technology, Beijing 100124, China
2 Beijing Water Affairs Information Management Center, Beijing 100038, China
a Corresponding author: 2795611970@qq.com
With the development of information technology, the construction of water resource system has been gradually carried out. In the background of big data, the work of water information needs to carry out the process of quantitative to qualitative change. Analyzing the correlation of data and exploring the deep value of data which are the key of water information’s research. On the basis of the research on the water big data and the traditional data warehouse architecture, we try to find out the connection of different data source. According to the temporal and spatial correlation of stagnant water and rainfall, we use spatial interpolation to integrate data of stagnant water and rainfall which are from different data source and different sensors, then use logistic regression to find out the relationship between them.
© Owned by the authors, published by EDP Sciences, 2017
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