Building Project-Based Teaching Model Based on BP Neural Network Associative Learning

DOI

10.2991/978-94-6463-242-2_72How to use a DOI?

Keywords

Project-Based Teaching; Associative Learning; BP Neural Network; Teaching Model

Abstract

The project-based teaching has become an effective model for training practical talents. BP neural networks learn to continuously adjust the network linkage weights and thresholds by propagating formulas to achieve minimum error control. Introducing BP neural network associative learning algorithm into Project-based teaching process design, through repeated training, the corresponding index weights are continuously adjusted to build a more ideal Project-based teaching model, then achieve the purpose of optimizing all aspects of the Project-based teaching process and ensuring the effective implementation of Project-based teaching.

Copyright

© 2024 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Yan Chen
AU  - Jun Zheng
AU  - Yalin Chen
PY  - 2023
DA  - 2023/09/22
TI  - Building Project-Based Teaching Model Based on BP Neural Network Associative Learning
BT  - Proceedings of the 2023 4th International Conference on Artificial Intelligence and Education (ICAIE 2023)
PB  - Atlantis Press
SP  - 591
EP  - 597
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-242-2_72
DO  - 10.2991/978-94-6463-242-2_72
ID  - Chen2023
ER  -