智能制造下智能教学系统Hadoop处理NetCDF数据的设备优化探讨  

Exploration of Device Optimization for Hadoop Processing NetCDF Data in Intelligent Teaching System under Intelligent Manufacturing

作　　者：陈晓红 任晓鸽 Chen Xiaohong;Ren Xiaoge(Xuchang Electrical Vocational College,Department of Information Engineering,Xuchang,Henan 460000,CHN)

机构地区：[1]许昌电气职业学院,河南许昌460000

出　　处：《模具制造》2024年第9期186-188,共3页Die & Mould Manufacture

基　　金：2021年中国高校产学研创新基金——新一代信息技术创新项目《基于Hadoop的NetCDF数据存储分析教学实训场景研究(编号2021ITA09018)》课题研究成果。

摘　　要：随着智能制造的快速发展,智能教学系统对大数据处理能力需求日益增长,Hadoop作为一种强大的分布式计算框架,其在处理NetCDF数据方面具有显著优势。围绕Hadoop在处理NetCDF数据中的作用进行深入探讨,首先探讨了智能制造下Hadoop在处理NetCDF数据方面的具体应用,其次提出了设备优化策略,旨在提升智能教学系统在智能制造环境下的数据处理效率和教学效果。With the rapid development of intelligent manufacturing,the demand for big data processing capabilities in intelligent teaching systems is increasing.As a powerful distributed computing framework,Hadoop has significant advantages in processing NetCDF data.This article delves into the role of Hadoop in processing NetCDF data.Firstly,it explores the specific application of Hadoop in processing NetCDF data under intelligent manufacturing,and then proposes device optimization strategies,aiming to improve the data processing efficiency and teaching effectiveness of intelligent teaching systems in intelligent manufacturing environments.

关 键 词：智能制造 智能教学系统 HADOOP NetCDF数据 

分 类 号：TP31[自动化与计算机技术—计算机软件与理论]