Design of Multimedia Vocal Music Education Data Integration System Based on Adaptive Genetic Algorithm

In order to solve the problems of low accuracy of data integration results, low integration efficiency, and easy confusion between different types of data in traditional methods, a multimedia vocal education data integration system based on adaptive genetic algorithm was designed. Specifically, the...

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Vydáno v:Security and communication networks Ročník 2021; s. 1 - 9
Hlavní autoři: Zhang, Hao-Lan, Yu, Peng-Jiang
Médium: Journal Article
Jazyk:angličtina
Vydáno: London Hindawi 02.08.2021
John Wiley & Sons, Inc
Témata:
Adaptive algorithms
Big Data
Communication
Communications networks
Confusion
Data base management systems
Data exchange
Data integration
Data processing
Data transmission
Decision making
Design
Education
Extensible Markup Language
Genetic algorithms
Java
Language
Learning
Modules
Multimedia
Music education
Registration
Systems design
Systems development
Teaching methods
Vocal music
ISSN:1939-0114, 1939-0122
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Shrnutí:In order to solve the problems of low accuracy of data integration results, low integration efficiency, and easy confusion between different types of data in traditional methods, a multimedia vocal education data integration system based on adaptive genetic algorithm was designed. Specifically, the designed system is divided into three parts: data source management module, system administrator module, and database management module. The synchronized multimedia vocal education data are first processed by the synchronous multimedia vocal education data processing and then integrated by an adaptive genetic algorithm. The experimental results show that the longest data transmission time of the system is 2.3 s, which is much lower than that of the traditional method, and the accuracy of the integration result is higher, and the probability of data integration confusion is lower, which all indicate that the designed system has better application performance.
Bibliografie:ObjectType-Article-1
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ISSN:1939-0114
1939-0122
DOI:10.1155/2021/3897696