Title: Advanced ideological and political education strategy based on artificial intelligence: edge computing method

Authors: Yue Zheng

Addresses: Huanghe Science and Technology University, Zhengzhou 450006, China

Abstract: Currently, advanced ideological and political education has developed rapidly. Based on transfer learning, deep neural networks (DNN) and edge computing, this paper analyses and studies an advanced recognition system of ideological and political education. We compare the precision and other indicators obtained from the training of AlexNet and ResNet deep learning models. It compares the suitability of the two models for identifying advanced ideological and political education. It deploys the ResNet model to the edge server, which can execute feature extraction and real-time detection. Finally, this paper carries out the simulation experiments on the above models and algorithms respectively. The ResNet deep learning model based on edge computing has a superior task completion rate compared to traditional deep learning algorithms and it has better practicability for advanced ideological and political education strategies.

Keywords: artificial intelligence; deep learning; edge computing; advanced ideological and political education strategy.

DOI: 10.1504/IJCEELL.2025.148694

International Journal of Continuing Engineering Education and Life-Long Learning, 2025 Vol.35 No.5, pp.420 - 434

Received: 08 Sep 2023
Accepted: 05 Mar 2024
Published online: 19 Sep 2025 *