摘要
随着信息技术的迅速发展,中职教育领域对计算机实验教学系统的要求日益提高。然而,现有系统在设备现代化、数据管理及设备维护等方面存在诸多不足。反向传播(Back Propagation,BP)神经网络作为一种高效的机器学习算法,为解决这些问题提供了新的思路和方法。本文分析中职计算机教学系统现状,阐述计算机实验教学系统的关键技术,探讨如何利用BP神经网络的自适应和自学习功能优化中职计算机实验教学系统,提升教学的互动性和个性化。
With the rapid development of information technology,the requirements of computer experimental teaching system in the field of secondary vocational education are increasing day by day.However,the existing system has many shortcomings in equipment modernization,data management and equipment maintenance.As an efficient machine learning algorithm,Back Propagation(BP)neural network provides a new idea and method to solve these problems.This paper analyzes the current situation of the computer teaching system in secondary vocational schools,expounds the key technologies of the computer experiment teaching system,and discusses how to optimize the computer experiment teaching system in secondary vocational schools by using the adaptive and self-learning functions of BP neural network to improve the interactive and personalized teaching.
作者
林丽华
LIN Lihua(Fujian Yongchun Vocational and Technical School,Quanzhou Fujian 362600,China)
出处
《信息与电脑》
2024年第10期243-245,249,共4页
Information & Computer
关键词
中职教育
计算机实验教学系统
BP神经网络
secondary vocational education
computer experimental teaching system
BP neural network
