Accurate recommendation model of mechanical engineering teaching resources for undergraduate students based on big data algorithm

Xianzhou Hou

doi:10.1117/12.2683014

16 June 2023 Accurate recommendation model of mechanical engineering teaching resources for undergraduate students based on big data algorithm

Xianzhou Hou

Author Affiliations +

Proceedings Volume 12703, Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023); 127030V (2023) https://doi.org/10.1117/12.2683014
Event: Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023), 2023, Hong Kong, China

Abstract

With the rapid development of science and technology, the characteristics of comprehensive intersection of modern mechanical disciplines are becoming more and more obvious. Strengthening professional knowledge education, innovative consciousness training, hands-on ability training and comprehensive quality training has become the basic requirement of talent training in mechanical discipline and the core content of contemporary higher education in mechanical discipline. In order to achieve "safe, efficient and high-quality" engineering construction and operation, it is urgent to apply intelligent algorithms to analyze and process engineering big data to provide support for decision-making and planning and design of engineering construction. These demands strongly drive colleges and universities to cultivate talents who understand engineering construction and have intelligent information thinking, which is also the main connotation of engineering professionals training under the background of new engineering. In order to improve students' interest and subjective initiative in learning this course, so that students can deeply understand and master the course knowledge and can learn and use it flexibly in practical engineering, this paper discusses the teaching content and teaching method of mechanical engineering materials course according to the characteristics of safety engineering specialty. The results show that the experimental system has complete functions and good operability and stability.

Citation Download Citation

Xianzhou Hou "Accurate recommendation model of mechanical engineering teaching resources for undergraduate students based on big data algorithm", Proc. SPIE 12703, Sixth International Conference on Intelligent Computing, Communication, and Devices (ICCD 2023), 127030V (16 June 2023); https://doi.org/10.1117/12.2683014

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available

Members: $17.00

Non-members: $21.00 ADD TO CART

PROCEEDINGS
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Engineering

Mechanical engineering

Control systems

Data modeling

Artificial intelligence

Evolutionary algorithms

Machine learning

Show All Keywords

Keywords/Phrases

Search In:

Publication Years