Abstract
In order to solve the problems of low prediction accuracy and long prediction time of traditional resource demand prediction methods, an online learning resource demand prediction method based on BP neural network is proposed. Online learning resources are collected, online learning resource management evaluation indicators are constructed, and online learning resource demand prediction algorithms are optimized. Finally, experiments show that the resource demand prediction accuracy of this method is higher than that of traditional methods, it can fully meet the requirements of online learning resource demand forecasting, and can help improve the efficiency and quality of online learning.
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Science and technology project of Jiangxi Provincial Department of education in 2019, Poject name:Research and implementation of intelligent delivery terminal based on mobile Internet and AI (GJJ191579).
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© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Huang, Y., Gao, J. (2022). Prediction of Online Learning Resource Demand Based on BP Neural Network. In: Fu, W., Sun, G. (eds) e-Learning, e-Education, and Online Training. eLEOT 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 454. Springer, Cham. https://doi.org/10.1007/978-3-031-21164-5_27
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DOI: https://doi.org/10.1007/978-3-031-21164-5_27
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