[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 …
Temporal regularized matrix factorization for high-dimensional time series prediction
Time series prediction problems are becoming increasingly high-dimensional in modern
applications, such as climatology and demand forecasting. For example, in the latter …
applications, such as climatology and demand forecasting. For example, in the latter …
HRST-LR: a hessian regularization spatio-temporal low rank algorithm for traffic data imputation
Intelligent Transportation Systems (ITSs) are vital for alleviating traffic congestion and
improving traffic efficiency. Due to the delay of network transmission and failure of detectors …
improving traffic efficiency. Due to the delay of network transmission and failure of detectors …
A compressive sensing-based approach to end-to-end network traffic reconstruction
Estimation of end-to-end network traffic plays an important role in traffic engineering and
network planning. The direct measurement of a network's traffic matrix consumes large …
network planning. The direct measurement of a network's traffic matrix consumes large …
GraphSAGE-based traffic speed forecasting for segment network with sparse data
Forecasting of traffic conditions plays a significant role in smart traffic management systems.
With the prevalent use of massive vehicle trajectory data, agencies inevitably encounter …
With the prevalent use of massive vehicle trajectory data, agencies inevitably encounter …
A nonconvex low-rank tensor completion model for spatiotemporal traffic data imputation
Sparsity and missing data problems are very common in spatiotemporal traffic data collected
from various sensing systems. Making accurate imputation is critical to many applications in …
from various sensing systems. Making accurate imputation is critical to many applications in …
Flow management and flow modeling in network clouds
M Malboubi, B Jiang - US Patent 10,656,960, 2020 - Google Patents
Assignment of network addresses and estimations of flow sizes associated with network
nodes can be enhanced. Assignment management component (AMC) partitions a set of …
nodes can be enhanced. Assignment management component (AMC) partitions a set of …
A reinforcement learning-based network traffic prediction mechanism in intelligent internet of things
Intelligent Internet of Things (IIoT) is comprised of various wireless and wired networks for
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …
industrial applications, which makes it complex and heterogeneous. The openness of IIoT …
Hierarchical data aggregation using compressive sensing (HDACS) in WSNs
Energy efficiency is one of the key objectives in data gathering in wireless sensor networks
(WSNs). Recent research on energy-efficient data gathering in WSNs has explored the use …
(WSNs). Recent research on energy-efficient data gathering in WSNs has explored the use …
Network traffic prediction based on deep belief network in wireless mesh backbone networks
Wireless mesh network is prevalent for providing a decentralized access for users. For a
wireless mesh backbone network, it has obtained extensive attention because of its large …
wireless mesh backbone network, it has obtained extensive attention because of its large …