Advanced Network Traffic Prediction Using Deep Learning Techniques: A Comparative Study of SVR, LSTM, GRU, and Bidirectional LSTM Models

Advanced Network Traffic Prediction Using Deep Learning Techniques: A Comparative Study of SVR, LSTM, GRU, and Bidirectional LSTM Models

Accurate prediction of network traffic patterns is essential for optimizing network resource allocation, managing congestion, and strengthening cybersecurity. This study examines the effectiveness of four machine learning models—Support Vector Regression (SVR), Long Short-Term Memory (LSTM), Gated R...

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Bibliographic Details
Main Author:	Wang Yuxin
Format:	Article
Language:	English
Published:	EDP Sciences 2025-01-01
Series:	ITM Web of Conferences
Online Access:	https://www.itm-conferences.org/articles/itmconf/pdf/2025/01/itmconf_dai2024_03021.pdf
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