Clustering Application for Streaming Big Data in Smart Grid

被引：0

作者：

Banga, Alisha ^{[1
]}

Sinha, Amrita ^{[2
]}

机构：

[1] Thapar Inst Engn & Technol, Patiala, Punjab, India

[2] Thapar Inst Engn & Technol, Dept EIED, Patiala, Punjab, India

来源：

PROCEEDINGS OF THE 2018 IEEE INTERNATIONAL CONFERENCE ON COMMUNICATION AND SIGNAL PROCESSING (ICCSP) | 2018年

关键词：

Big Data; Clustering; Machine Learning; streaming data;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Due to much advancement in technologies and a strong recommendation from both economic and environmental issues, the traditional power grid is updated to a new smart grid that allows two-way communications as well as monitors the system for system stability. It also enables integration of distributed energy sources and can also schedule energy consumption for its customers. Due to this up gradation, there is a tremendous amount of big data that has to be considered for further analysis of the system regarding faults; energy consumption etc. This paper presents a data mining approach applied to streaming data sets. The authors have used a software environment 'Python' for carrying out the unsupervised data mining processes.

引用

页码：1051 / 1054

页数：4

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