Research on two-way intelligent self-service system of electric power business hall applying data compression algorithm

This paper applies a data compression algorithm to designing a two-way intelligent self-service system for an electric power business hall and proposes a multiwavelet embedded zero-tree coding method and compression of electric power data. Based on the multiwavelet transform, a multiwavelet threshol...

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Vydáno v:Applied mathematics and nonlinear sciences Ročník 9; číslo 1
Hlavní autoři: Zhou, Baowei, Lin, Yongxiang, Cao, Sheng, Su, Hongbang, Qi, Xiaoxuan, Zhang, Yaling
Médium: Journal Article
Jazyk:angličtina
Vydáno: Beirut Sciendo 01.01.2024
De Gruyter Brill Sp. z o.o., Paradigm Publishing Services
Témata:
78-02
Data compression algorithm
Electric power business hall
Electric power data
Intelligent self-service
Multiwavelet transform
ISSN:2444-8656, 2444-8656
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Shrnutí:This paper applies a data compression algorithm to designing a two-way intelligent self-service system for an electric power business hall and proposes a multiwavelet embedded zero-tree coding method and compression of electric power data. Based on the multiwavelet transform, a multiwavelet threshold power data compression algorithm is proposed, and the decomposition reconstruction comparison of the multiwavelet transform, and the implementation process of the compression algorithm are discussed. The implementation effect of the electric power intelligent business hall is discussed through the evaluation analysis of the service before and after the intelligent business hall. The results show that the platform operation effect score of the electric power intelligent service management platform project of company H is 0.8723. This paper's platform design and implementation provide useful research references for improving the service quality and efficiency of the electric power business hall.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2444-8656
2444-8656
DOI:10.2478/amns.2023.2.00704