Open AccessResearch on Distributed Photovoltaic Power Station Builders Segmentation Based on Data Mining
Author(s) -
Ke Yang,
Hejian Wang,
Junsheng Wang,
Shaozhen Chen
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1626/1/012062
Subject(s) - subdivision , photovoltaic system , value (mathematics) , computer science , cluster analysis , investment (military) , investment value , power (physics) , data mining , operations research , engineering , civil engineering , electrical engineering , business , artificial intelligence , machine learning , finance , cash , politics , law , political science , physics , quantum mechanics
Simply according to the investment scale of distributed photovoltaic power station builders, the subdivision of the builder fails to fully consider their potential value, thus underestimating the contribution of the builder to the e-commerce platform. This paper constructs the value index evaluation system of the distributed photovoltaic power station from the current value and potential value of the builders. Based on the objective data of the builders and the clustering algorithm, this paper establishes a two-dimensional subdivision model of the builders based on the current value and potential value of the builders. This paper proposes specific marketing strategies for the value characteristics of each type of builders, which provides a scientific basis for e-commerce platform marketing decisions.