Work

Network Traffic Prediction Mechanism Based on Variational Mode Decomposition and GA-ELM

Year: 2024

Type: conference-paper

Abstract: Accurate prediction of network traffic is crucial to network resource management, whether it's network resource provisioning or malicious attack detection, reliable network traffic prediction mechanisms are needed for advance warning existing network traffic prediction methods still have some obvious limitations, existing network traffic prediction methods still have some obvious limitations, such as high computational complexity, VMD decomposition parameter optimization problem, premature convergence into local optimum solutions, and integrated prediction model prediction accuracy is not high many problems. In response to the above, this paper presents a model that combines Variation Mode Decomposition (VMD) and Extreme Learning Machine (ELM) for predicting network traffic based on Genetic Algorithm (GA).

Source: International Conference on Electronic Information Technology and Computer Engineering (EITCE)

DOI: 10.1145/3711129.3711293

Authors: Jinghe Zhou, Jinmei Shi, Xue Chen, Mengyao Chen

Institution: Hainan Vocational University of Science and Technology

Language: English

Topic: Machine Learning and ELM

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: bronze

Funder: National Natural Science Foundation of China