Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019)

Analysis of PV Poverty Alleviation Users Based on Big Data

Authors
Jian Li
Corresponding Author
Jian Li
Available Online May 2019.
DOI
10.2991/cnci-19.2019.10How to use a DOI?
Keywords
Photovoltaic poverty alleviation, logistic regression algorithm,user label, index system.
Abstract

Based on the historical data of power customers, the index system needed to determine the model is determined based on the customer's basic attributes, power usage behavior, payment behavior, customer credit, geographic region, and weather environment. Through the correlation coefficient matrix and information value (IV) of the indicator, the index variables that finally enter the model are selected, the variables are grouped by the optimal grouping method and the weight of Evidence (WOE) is transformed. Based on the processed data, the logistic regression algorithm is used to construct the PV poverty alleviation user analysis model, and the users are classified into high, medium and low grade suspected poor users according to the analysis model, and the analysis results are fed back to the government's poverty alleviation office for confirmation feedback. This paper provide a basis for selecting poor households in the Xinjiang Poverty Alleviation Competition.

Copyright
© 2019, 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 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019)
Series
Advances in Computer Science Research
Publication Date
May 2019
ISBN
10.2991/cnci-19.2019.10
ISSN
2352-538X
DOI
10.2991/cnci-19.2019.10How to use a DOI?
Copyright
© 2019, 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  - Jian Li
PY  - 2019/05
DA  - 2019/05
TI  - Analysis of PV Poverty Alleviation Users Based on Big Data
BT  - Proceedings of the 2019 International Conference on Computer, Network, Communication and Information Systems (CNCI 2019)
PB  - Atlantis Press
SP  - 74
EP  - 82
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnci-19.2019.10
DO  - 10.2991/cnci-19.2019.10
ID  - Li2019/05
ER  -