Real-Time Visualization Optimization Management Simulation of Big Data Stream on Industrial Heritage Cloud Platform

Mengya Gao

Complexity, 2020, vol. 2020, 1-10

Abstract:

Recently, the development and utilization of industrial heritage resources by using big data has gradually attracted attention. This paper proposes a real-time visualization optimization management simulation of an industrial heritage cloud platform, which realizes the high reliability and diversified storage and utilization of industrial big data by the cloud data distributed storage subsystem. The big data prediction model of the GRU neural network based on a spark distributed framework is constructed to realize the prediction of industrial genetic data. Finally, visualization technology can provide information supporting for industrial production by displaying effective information intuitively. The model’s effectiveness and reliability are verified by simulation.

Date: 2020
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/8503/2020/8885191.pdf (application/pdf)
http://downloads.hindawi.com/journals/8503/2020/8885191.xml (text/xml)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hin:complx:8885191

DOI: 10.1155/2020/8885191

Access Statistics for this article

More articles in Complexity from Hindawi
Bibliographic data for series maintained by Mohamed Abdelhakeem ().