Machine (deep) learning-enabled accurate traffic modeling and prediction is an
indispensable part for future big data-driven intelligent cellular networks, since it can help …

Traffic congestion is a widely recognized challenging problem that is increasingly growing
around the world. This paper leverages ARIMA-based modeling to study some factors that …

Analyzing network traffic behavior is essential for detecting network anomalies. However, it
remains a challenge to effectively analyze this behavior for anomaly diagnosis. One …

Modeling and forecasts of global oceanographic index has important implications for
decision making. An effective management on climate anomalies impact depends on the …

Developing prediction models for mobile networks have been increasing in recent years, in
response to the ever increasing volumes of customer traffic and also to understand the …

To pursue a superior modeling tools for improving the predictive efficacy in Indian Ocean
Dipole Index (IOD) using a hybrid time series model. A methods which makes use of …

This paper deals with the Estimation of the Traffic Matrix (TM) of the well-known American
ABILENE IP Network also called Internet 2. This work which has been processed on real …

ネットワークの大規模化や通信サービスの多様化に伴い, 機械学習/AI 技術を活用したネットワーク
運用管理の高度化が期待されている. 本論文では, ネットワークの自動監視においてより高精度な …