The 𝜶 Parameter in the Generalized Choquet Integral for Network Traffic Prediction

• Abreu Quevedo Federal University of Rio Grande (FURG)
• Denner Ayres Federal University of Rio Grande (FURG) https://orcid.org/0009-0006-4494-7898
• Graçaliz Dimuro Federal University of Rio Grande (FURG)
• Giancarlo Lucca Catholic University of Pelotas (UCPel)
• André Riker Federal University of Pará (UFPA) https://orcid.org/0009-0006-8864-9948
• Bruno L. Dalmazo Federal University of Rio Grande (FURG) https://orcid.org/0000-0002-6996-7602

DOI: https://doi.org/10.5753/errc.2024.4627

Abstract

Network traffic is crucial to the functioning of modern life, and predicting and measuring this traffic is a valuable strategic asset that requires deep knowledge of algorithms and technology. Several models, such as fuzzy c-means and regression, attempt to solve this issue but still do not achieve optimal performance. This paper proposes an aggregation model based on the variation of the 𝛼 parameter in the Choquet integral, aiming to measure the errors associated with each 𝛼 value to identify the best method and parameter for optimizing the equations.

Keywords: Search models, Choquet integral, Network traffic prediction

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