Multi-source Intelligent Management System of College Snow and Ice Teaching Based on Cloud Platform

ChongYu Yi, Yongqiang Liu, Zhao Zhiqiang and Naeem Jan

Mathematical Problems in Engineering, 2022, vol. 2022, 1-8

Abstract: The conventional college snow and ice teaching multi-source resource intelligent management system has the problem of incomplete software resource analysis function, which leads to high CPU usage of system. A cloud platform based college snow and ice teaching multi-source resource intelligent management system is designed. Hardware part: record the state of the pins when the register is reset, account for the data bit width and storage capacity of DDR2 SDRAM memory, and optimise the data storage module; Part of the software: obtain ice and snow sports course objectives in colleges and universities, rationally organise the course organization form, optimise the intelligent management mode of teaching multi-source resources by using the cloud platform, support online browsing of various text resources, set relevant parameters to construct various random modification operations, and design the software resource analysis function with the knowledge fusion algorithm. Experimental results: The average CPU usage of the multi-source intelligent resource management system for snow and ice teaching in colleges and universities in this paper and the other two systems is 34.257%, 47.458%, 53.578%. Experimental results show that the performance of multi-source intelligent resource management system for snow and ice teaching in colleges and universities has been significantly improved after making full use of cloud platform.

Date: 2022
References: Add references at CitEc
Citations:

Downloads: (external link)
http://downloads.hindawi.com/journals/mpe/2022/9881970.pdf (application/pdf)
http://downloads.hindawi.com/journals/mpe/2022/9881970.xml (application/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:jnlmpe:9881970

DOI: 10.1155/2022/9881970

Access Statistics for this article

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