[PDF][PDF] Metaheuristic Optimization of Time Series Models for Predicting Networks Traffic
R Alkanhel, ESM El-kenawy… - CMC-COMPUTERS …, 2023 - researchgate.net
Traffic prediction of wireless networks attracted many researchers and practitioners during
the past decades. However, wireless traffic frequently exhibits strong nonlinearities and …
the past decades. However, wireless traffic frequently exhibits strong nonlinearities and …
Intelligent hybrid model to enhance time series models for predicting network traffic
Network traffic analysis and predictions have become vital for monitoring networks. Network
prediction is the process of capturing network traffic and examining it deeply to decide what …
prediction is the process of capturing network traffic and examining it deeply to decide what …
An autonomous resource provisioning framework for massively multiplayer online games in cloud environment
M Ghobaei-Arani, R Khorsand… - Journal of Network and …, 2019 - Elsevier
Abstract Massively Multiplayer Online Games (MMOGs) applications are a class of
computationally intensive client-server multi-tier applications with real-time quality of service …
computationally intensive client-server multi-tier applications with real-time quality of service …
A new hybrid method for time series forecasting: AR–ANFIS
B Sarıca, E Eğrioğlu, B Aşıkgil - Neural Computing and Applications, 2018 - Springer
In this study, a new hybrid forecasting method is proposed. The proposed method is called
autoregressive adaptive network fuzzy inference system (AR–ANFIS). AR–ANFIS can be …
autoregressive adaptive network fuzzy inference system (AR–ANFIS). AR–ANFIS can be …
Robust fuzzy regression functions approaches
E Bas - Information Sciences, 2022 - Elsevier
In the structure of fuzzy inference systems, the decision-making process is based on certain
rules called “if-then”. It is highly difficult to determine these rules. The fuzzy regression …
rules called “if-then”. It is highly difficult to determine these rules. The fuzzy regression …
Recurrent type-1 fuzzy functions approach for time series forecasting
Forecasting the future values of a time series is a common research topic and is studied
using probabilistic and non-probabilistic methods. For probabilistic methods, the …
using probabilistic and non-probabilistic methods. For probabilistic methods, the …
Prediction of industrial debutanizer column compositions using data-driven ANFIS-and ANN-based approaches
The work in this paper is based on an industrial debutanizer column in a petroleum refinery
located in Malaysia, which produces LPG (liquefied petroleum gas) as the top stream and …
located in Malaysia, which produces LPG (liquefied petroleum gas) as the top stream and …
Comparative evaluation of ARIMA and ANFIS for modeling of wireless network traffic time series
RK Yadav, M Balakrishnan - EURASIP Journal on Wireless …, 2014 - Springer
Network traffic modeling significantly affects various considerations in networking, including
network resource allocation, quality of service provisioning, network traffic management …
network resource allocation, quality of service provisioning, network traffic management …
Integration of time series models with soft clustering to enhance network traffic forecasting
THH Aldhyani, MR Joshi - 2016 Second International …, 2016 - ieeexplore.ieee.org
The network traffic forecasting is of significant interest in many domains such as bandwidth
allocation, congestion control and network management. Hence, forecasting of network …
allocation, congestion control and network management. Hence, forecasting of network …
Long-term prediction of Iranian blood product supply using LSTM: a 5-year forecast
E Miri-Moghaddam, SK Bizhaem, Z Moezzifar… - BMC Medical Informatics …, 2024 - Springer
Background This study aims to predict the trend of procurement and storage of various blood
products, as well as planning and monitoring the consumption of blood products in different …
products, as well as planning and monitoring the consumption of blood products in different …