Research on The Design of Power Enterprise Central Data Platform Framework Based on Big Data

Author:

Shen Liang,Cheng Zhihua,Gao Lingchao,Luo Yiwang,Cai Yuxiang

Abstract

Abstract With the rapid development of computer technology and Internet, the traditional data mining methods and technologies in power industry will face great difficulties, and it is difficult to carry out accurate data processing and analysis. How to mine valuable data from a large number of original data has become a research difficulty. Aiming at this problem, this paper establishes the framework design of power enterprise central data platform based on big data. In order to further improve the actual performance of the scheme, the defects of existing algorithms are analyzed by IM_Apriori improves the calculation method, simplifies the calculation steps, reduces the calculation times, and provides technical support for enterprise data analysis. Through the analysis of the test results, when the data peak reaches 100 m, the execution time is reduced by 25s, which is obviously superior to the traditional scheme. The test results show that the design scheme in this paper has a high comprehensive performance, compared with the traditional central data platform framework, the performance has been greatly improved. Through the analysis, the research in this paper has achieved ideal results, and has made a contribution to the research on the framework design of the central data platform of power enterprises.

Publisher

IOP Publishing

Subject

General Engineering

Reference10 articles.

1. Development of the optimization framework for low-power wireless power transfer systems;Lee;IEEE Transactions on Microwave Theory & Techniques,2015

2. Determinants of bank profits and its persistence in indian banks: a study in a dynamic panel data framework;Sinha;International Journal of System Assurance Engineering & Management,2016

3. An extension of the j-test to a spatial panel data framework;Kelejian;Journal of Applied Econometrics,2016

4. Need for comprehending ground water nature utilizing geological data framework-a study report;Basha;International Journal of Civil Engineering,2018

5. Data security framework for data-centers;Kumar;International Journal Of Computer Ences And Engineering,2019

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