On the public citation graph

Long-Term Mobile Traffic Forecasting Using Deep Spatio-Temporal Neural Networks

https://doi.org/10.1145/3209582.3209606
0 signed · 297 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1016/j.comcom.2010.08.008openalex-snapshot
Dynamic bandwidth provisioning using ARIMA-based traffic forecasting for Mobile WiMAX
inferredcites →https://doi.org/10.1016/j.neucom.2013.03.047openalex-snapshot
Time series forecasting using a deep belief network with restricted Boltzmann machines
inferredcites →https://doi.org/10.1038/s41598-018-24271-9openalex-snapshot
Recurrent Neural Networks for Multivariate Time Series with Missing Values
inferredcites →https://doi.org/10.1038/sdata.2015.55openalex-snapshot
A multi-source dataset of urban life in the city of Milan and the Province of Trentino
inferredcites →https://doi.org/10.1109/asru.2013.6707742openalex-snapshot
Hybrid speech recognition with Deep Bidirectional LSTM
inferredcites →https://doi.org/10.1109/comst.2015.2491361openalex-snapshot
Large-Scale Mobile Traffic Analysis: A Survey
inferredcites →https://doi.org/10.1109/infcom.2003.1208954openalex-snapshot
Long-term forecasting of Internet backbone traffic: observations and initial models
inferredcites →https://doi.org/10.1109/infocom.2017.8057089openalex-snapshot
Joint spatial and temporal classification of mobile traffic demands
inferredcites →https://doi.org/10.1109/infocom.2017.8057090openalex-snapshot
Spatiotemporal modeling and prediction in cellular networks: A big data enabled deep learning approach
inferredcites →https://doi.org/10.1109/mcom.2014.6829969openalex-snapshot
The prediction analysis of cellular radio access network traffic: From entropy theory to networking practice
inferredcites →https://doi.org/10.1109/softcom.2007.4446113openalex-snapshot
Traffic prediction for mobile network using Holt-Winter’s exponential smoothing
inferredcites →https://doi.org/10.1109/tnet.2007.893217openalex-snapshot
ARCH-Based Traffic Forecasting and Dynamic Bandwidth Provisioning for Periodically Measured Nonstationary Traffic
inferredcites →https://doi.org/10.1109/tpami.2012.59openalex-snapshot
3D Convolutional Neural Networks for Human Action Recognition
inferredcites →https://doi.org/10.1109/tsc.2016.2599878openalex-snapshot
Big Data Driven Mobile Traffic Understanding and Forecasting: A Time Series Approach
inferredcites →https://doi.org/10.1126/science.304.5667.34openalex-snapshot
Learning to Forget
inferredcites →https://doi.org/10.1145/1273496.1273596openalex-snapshot
Restricted Boltzmann machines for collaborative filtering
inferredcites →https://doi.org/10.1145/1390156.1390177openalex-snapshot
A unified architecture for natural language processing
inferredcites →https://doi.org/10.1145/2815675.2815680openalex-snapshot
Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment
inferredcites →https://doi.org/10.1145/2835487openalex-snapshot
3D Mesh Labeling via Deep Convolutional Neural Networks
inferredcites →https://doi.org/10.1145/3065386openalex-snapshot
ImageNet classification with deep convolutional neural networks
inferredcites →https://doi.org/10.1145/3123266.3129391openalex-snapshot
TensorLayer
inferredcites →https://doi.org/10.1145/3143361.3143393openalex-snapshot
ZipNet-GAN
inferredcites →https://doi.org/10.1162/089976600300015015openalex-snapshot
Learning to Forget: Continual Prediction with LSTM
inferredcites →https://doi.org/10.1184/r1/6554699openalex-snapshot
Efficient Reductions for Imitation Learning
inferredcites →https://doi.org/10.1287/mnsc.6.3.324openalex-snapshot
Forecasting Sales by Exponentially Weighted Moving Averages
inferredcites →https://doi.org/10.4230/oasics.dx.2026.15openalex-snapshot
AutoResearch Lite: a reproducible paper-inspired experiment runner (Adam mechanism reproduction and convergence-speed comparison)
inferredcites →https://doi.org/10.48550/arxiv.1409.3215openalex-snapshot
Sequence to Sequence Learning with Neural Networks
inferredcites →https://doi.org/10.48550/arxiv.1506.04214openalex-snapshot
Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting
inferredcites →https://doi.org/10.48550/arxiv.1603.04467openalex-snapshot
TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4615081openalex-extracted
inferred← citeshttps://doi.org/10.2139/ssrn.4827065openalex-extracted
inferred← citeshttps://doi.org/10.1002/9781119562306.ch7openalex-snapshot
Deep Learning Based Traffic and Mobility Prediction
inferred← citeshttps://doi.org/10.1002/ett.4860openalex-snapshot
An optimized hybrid methodology for short‐term traffic forecasting in telecommunication networks
inferred← citeshttps://doi.org/10.1002/nem.2191openalex-snapshot
Predicting short‐term mobile Internet traffic from Internet activity using recurrent neural networks
inferred← citeshttps://doi.org/10.1002/spe.3386openalex-snapshot
Federated Learning‐Based Mobile Traffic Prediction in Satellite‐Terrestrial Integrated Networks
inferred← citeshttps://doi.org/10.1007/978-3-030-19945-6_10openalex-snapshot
Delmu: A Deep Learning Approach to Maximising the Utility of Virtualised Millimetre-Wave Backhauls
inferred← citeshttps://doi.org/10.1007/978-3-030-99191-3_2openalex-snapshot
A Survey of Traffic Prediction Based on Deep Neural Network: Data, Methods and Challenges
inferred← citeshttps://doi.org/10.1007/978-981-15-6390-4_18openalex-snapshot
Machine Learning in 5G Wireless Networks
inferred← citeshttps://doi.org/10.1007/978-981-16-0289-4_3openalex-snapshot
LSTM Network for Hotspot Prediction in Traffic Density of Cellular Network
inferred← citeshttps://doi.org/10.1007/978-981-92-3551-3_10openalex-snapshot
STWPN: A Spatio-Temporal Graph Neural Network for Water Level Prediction in Underground Pipeline Networks
inferred← citeshttps://doi.org/10.1007/978-981-99-0483-9_22openalex-snapshot
Review on Deep Learning in Wireless Communication Networks
inferred← citeshttps://doi.org/10.1007/978-981-99-8388-9_22openalex-snapshot
Spatial Bottleneck Transformer for Cellular Traffic Prediction in the Urban City
inferred← citeshttps://doi.org/10.1007/s00500-022-07718-0openalex-snapshot
A stacked broad learning system with multitask learning method for cellular wireless network traffic prediction
inferred← citeshttps://doi.org/10.1007/s10489-023-04871-3openalex-snapshot
DyGCN-LSTM: A dynamic GCN-LSTM based encoder-decoder framework for multistep traffic prediction
inferred← citeshttps://doi.org/10.1007/s10515-022-00349-7openalex-snapshot
Mobile traffic flow prediction using intelligent whale optimization algorithm
inferred← citeshttps://doi.org/10.1007/s10707-024-00517-9openalex-snapshot
Foresight plus: serverless spatio-temporal traffic forecasting
inferred← citeshttps://doi.org/10.1007/s11227-021-03662-2openalex-snapshot
A lightweight model with spatial–temporal correlation for cellular traffic prediction in Internet of Things
inferred← citeshttps://doi.org/10.1007/s11227-023-05388-9openalex-snapshot
Identify spatio-temporal properties of network traffic by model checking
inferred← citeshttps://doi.org/10.1007/s12243-022-00940-9openalex-snapshot
A novel network traffic prediction method based on a Bayesian network model for establishing the relationship between traffic and population
inferred← citeshttps://doi.org/10.1007/s12652-020-02209-2openalex-snapshot
Wireless backhaul network’s capacity optimization using time series forecasting approach
inferred← citeshttps://doi.org/10.1007/s41870-024-02028-0openalex-snapshot
Cellular Data Analysis using Machine Learning for Crowd Gathering Prediction
inferred← citeshttps://doi.org/10.1007/s42486-025-00192-1openalex-snapshot
A context knowledge guided transformer framework for long-term traffic prediction
inferred← citeshttps://doi.org/10.1016/b978-0-443-18424-6.00005-2openalex-snapshot
Multi-data-based travel behavior analysis and prediction
inferred← citeshttps://doi.org/10.1016/j.adhoc.2020.102258openalex-snapshot
A deep learning method based on an attention mechanism for wireless network traffic prediction
inferred← citeshttps://doi.org/10.1016/j.adhoc.2026.104380openalex-snapshot
Wireless network traffic prediction—A comprehensive survey on patterns, methodologies, and open issues
inferred← citeshttps://doi.org/10.1016/j.asoc.2022.109694openalex-snapshot
Long-term prediction of multiple types of time-varying network traffic using chunk-based ensemble learning
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.112698openalex-snapshot
Graph enhanced spatial–temporal transformer for traffic flow forecasting
inferred← citeshttps://doi.org/10.1016/j.comcom.2021.01.021openalex-snapshot
Deep Learning for Network Traffic Monitoring and Analysis (NTMA): A Survey
inferred← citeshttps://doi.org/10.1016/j.comnet.2020.107556openalex-snapshot
Towards artificial intelligence enabled 6G: State of the art, challenges, and opportunities
inferred← citeshttps://doi.org/10.1016/j.comnet.2021.108529openalex-snapshot
Packet-level prediction of mobile-app traffic using multitask Deep Learning
inferred← citeshttps://doi.org/10.1016/j.eng.2021.07.013openalex-snapshot
The SOLIDS 6G Mobile Network Architecture: Driving Forces, Features, and Functional Topology
inferred← citeshttps://doi.org/10.1016/j.engappai.2022.105472openalex-snapshot
A review of the use of artificial intelligence methods in infrastructure systems
inferred← citeshttps://doi.org/10.1016/j.eswa.2022.117163openalex-snapshot
Cellular traffic prediction with machine learning: A survey
inferred← citeshttps://doi.org/10.1016/j.inffus.2023.102079openalex-snapshot
Spatial–temporal graph neural network traffic prediction based load balancing with reinforcement learning in cellular networks
inferred← citeshttps://doi.org/10.1016/j.inffus.2024.102872openalex-snapshot
ST-MambaSync: Complement the power of Mamba and Transformer fusion for less computational cost in spatial–temporal traffic forecasting
inferred← citeshttps://doi.org/10.1016/j.knosys.2026.117104openalex-snapshot
Spatial–Temporal Key Node Graph Attention Network with Positional Encoding for traffic flow forecasting
inferred← citeshttps://doi.org/10.1016/j.neucom.2020.05.036openalex-snapshot
Toward effective mobile encrypted traffic classification through deep learning
inferred← citeshttps://doi.org/10.1016/j.phycom.2024.102420openalex-snapshot
Mobile traffic prediction with attention-based hybrid deep learning
inferred← citeshttps://doi.org/10.1016/j.physa.2025.130665openalex-snapshot
Light attention-based neural networks for traffic flow prediction
inferred← citeshttps://doi.org/10.1016/j.trc.2025.105501openalex-snapshot
Transferability in data poisoning attacks on spatiotemporal traffic forecasting models
inferred← citeshttps://doi.org/10.1016/j.treng.2024.100252openalex-snapshot
Intelligent transportation systems for sustainable smart cities
inferred← citeshttps://doi.org/10.1049/itr2.12400openalex-snapshot
Short‐term traffic flow prediction based on AST‐MTL‐CNN‐GRU
inferred← citeshttps://doi.org/10.1051/itmconf/20257001011openalex-snapshot
The Application Prospects of Event Data in Traffic Flow Prediction
inferred← citeshttps://doi.org/10.1080/13658816.2025.2451306openalex-snapshot
CSSKL: Collaborative Specific-Shared Knowledge Learning framework for cross-city spatiotemporal forecasting in cellular networks
inferred← citeshttps://doi.org/10.1080/13658816.2025.2506528openalex-snapshot
Learning dynamic relational heterogeneity for spatiotemporal prediction with geographical meta-knowledge
inferred← citeshttps://doi.org/10.1109/access.2019.2929430openalex-snapshot
Exploring Trajectory Prediction Through Machine Learning Methods
inferred← citeshttps://doi.org/10.1109/access.2019.2941110openalex-snapshot
The Mammoth Internet: Are We Ready?
inferred← citeshttps://doi.org/10.1109/access.2020.2970224openalex-snapshot
Capacity and Frequency Optimization of Wireless Backhaul Network Using Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/access.2020.2980597openalex-snapshot
BSENet: A Data-Driven Spatio-Temporal Representation Learning for Base Station Embedding
inferred← citeshttps://doi.org/10.1109/access.2020.3009169openalex-snapshot
Intelligent Hybrid Model to Enhance Time Series Models for Predicting Network Traffic
inferred← citeshttps://doi.org/10.1109/access.2020.3025210openalex-snapshot
Traffic Prediction of Wireless Cellular Networks Based on Deep Transfer Learning and Cross-Domain Data
inferred← citeshttps://doi.org/10.1109/access.2020.3032344openalex-snapshot
Driver Behavior Recognition via Interwoven Deep Convolutional Neural Nets With Multi-Stream Inputs
inferred← citeshttps://doi.org/10.1109/access.2020.3041765openalex-snapshot
Machine Learning Meets Communication Networks: Current Trends and Future Challenges
inferred← citeshttps://doi.org/10.1109/access.2021.3078113openalex-snapshot
A Deep-Learning Model for Estimating the Impact of Social Events on Traffic Demand on a Cell Basis
inferred← citeshttps://doi.org/10.1109/access.2021.3088423openalex-snapshot
Feature-Based Deep Neural Networks for Short-Term Prediction of WiFi Channel Occupancy Rate
inferred← citeshttps://doi.org/10.1109/access.2022.3166844openalex-snapshot
Proactive Radar Protection System in Shared Spectrum via Forecasting Secondary User Power Levels
inferred← citeshttps://doi.org/10.1109/access.2022.3230660openalex-snapshot
RTS-GAT: Spatial Graph Attention-Based Spatio-Temporal Flow Prediction for Big Data Retailing
inferred← citeshttps://doi.org/10.1109/access.2023.3236261openalex-snapshot
Forecasting Network Traffic: A Survey and Tutorial With Open-Source Comparative Evaluation
inferred← citeshttps://doi.org/10.1109/access.2023.3297143openalex-snapshot
Spatial-Temporal Correlation Neural Network for Long Short-Term Demand Forecasting During COVID-19
inferred← citeshttps://doi.org/10.1109/access.2024.3368854openalex-snapshot
Artificial Intelligence-Enabled 5G Network Performance Evaluation With Fine Granularity and High Accuracy
inferred← citeshttps://doi.org/10.1109/access.2024.3518483openalex-snapshot
Mobile Traffic Prediction at the Edge through Distributed and Deep Transfer Learning
inferred← citeshttps://doi.org/10.1109/access.2025.3580176openalex-snapshot
Future Open Networks Cross-Domain Cognitive Orchestration: A Novel Design Paradigm
inferred← citeshttps://doi.org/10.1109/balkancom58402.2023.10167893openalex-snapshot
Multivariate and Multi-step Traffic Prediction for NextG Networks with SLA Violation Constraints
inferred← citeshttps://doi.org/10.1109/bdcat63179.2024.00045openalex-snapshot
Efficient Node Reduction Heuristic for GNN-Based Traffic Speed Forecasting
inferred← citeshttps://doi.org/10.1109/bibm62325.2024.10821884openalex-snapshot
Exploring Natural Language Processing Model Acceleration in Molecular Dynamics Simulation Using High-Performance Computing and Machine Learning
inferred← citeshttps://doi.org/10.1109/bigcomp68355.2026.00012openalex-snapshot
Bridging Trend and Periodic Feature for Long-Term Time Series Forecasting
inferred← citeshttps://doi.org/10.1109/bigdata55660.2022.10036330openalex-snapshot
Sparse Spatio-Temporal Neural Network for Large-Scale Forecasting
inferred← citeshttps://doi.org/10.1109/cec60901.2024.10612119openalex-snapshot
Optimization of Node Reduction Using BRKGA for GNN-Based Traffic Speed Forecasting
inferred← citeshttps://doi.org/10.1109/ciss53076.2022.9751165openalex-snapshot
Multivariate Spatio-temporal Cellular Traffic Prediction with Handover Based Clustering
inferred← citeshttps://doi.org/10.1109/comst.2019.2904897openalex-snapshot
Deep Learning in Mobile and Wireless Networking: A Survey
inferred← citeshttps://doi.org/10.1109/comst.2022.3142532openalex-snapshot
A Survey on 5G Radio Access Network Energy Efficiency: Massive MIMO, Lean Carrier Design, Sleep Modes, and Machine Learning
inferred← citeshttps://doi.org/10.1109/comst.2023.3273121openalex-snapshot
Machine Learning for Service Migration: A Survey
inferred← citeshttps://doi.org/10.1109/comst.2024.3352910openalex-snapshot
Federated Learning-Empowered Mobile Network Management for 5G and Beyond Networks: From Access to Core
inferred← citeshttps://doi.org/10.1109/confluence51648.2021.9377107openalex-snapshot
Recognizing Massive Mobile Traffic Patterns to Understand Urban Dynamics
inferred← citeshttps://doi.org/10.1109/csci46756.2018.00177openalex-snapshot
Deep Learning at the Edge
inferred← citeshttps://doi.org/10.1109/csndsp54353.2022.9907909openalex-snapshot
Prediphant: Short Term Heavy User Prediction
inferred← citeshttps://doi.org/10.1109/ecice59523.2023.10383092openalex-snapshot
Reinforcement Learning for Dynamic Channel Assignment Using Predicted Mobile Traffic
inferred← citeshttps://doi.org/10.1109/eiect64462.2024.10866348openalex-snapshot
Enhancing Urban Traffic Forecasting with Scalable, Privacy-Preserving Federated Learning Approach
inferred← citeshttps://doi.org/10.1109/etaact69135.2026.11541775openalex-snapshot
NARNET-Based Traffic Prediction for Dynamic Spectrum Allocation: A Pre-FLATS-5G Baseline Study
inferred← citeshttps://doi.org/10.1109/eucnc/6gsummit51104.2021.9482498openalex-snapshot
Forecasting Wireless Network Traffic and Channel Utilization Using Real Network/Physical layer Data
inferred← citeshttps://doi.org/10.1109/eucnc/6gsummit58263.2023.10188244openalex-snapshot
MLOps meets Edge Computing: an Edge Platform with Embedded Intelligence towards 6G Systems
inferred← citeshttps://doi.org/10.1109/eucnc/6gsummit68295.2026.11577243openalex-snapshot
Development and Verification of Data-Driven Models for Traffic Forecasting to Support 6G Network Orchestration and Management
inferred← citeshttps://doi.org/10.1109/fmec59375.2023.10306017openalex-snapshot
Towards Energy-Aware Federated Traffic Prediction for Cellular Networks
inferred← citeshttps://doi.org/10.1109/gecost55694.2022.10010687openalex-snapshot
DeepRANKPI: Time Series KPIs Prediction in a Live Cellular Network with RNN
inferred← citeshttps://doi.org/10.1109/globecom38437.2019.9013136openalex-snapshot
Graph Attention Spatial-Temporal Network for Deep Learning Based Mobile Traffic Prediction
inferred← citeshttps://doi.org/10.1109/globecom46510.2021.9685204openalex-snapshot
One for All: Traffic Prediction at Heterogeneous 5G Edge with Data-Efficient Transfer Learning
inferred← citeshttps://doi.org/10.1109/globecom46510.2021.9685639openalex-snapshot
Mobile Traffic Forecasting for Green 5G Networks
inferred← citeshttps://doi.org/10.1109/globecom46510.2021.9685804openalex-snapshot
Spider: Deep Learning-driven Sparse Mobile Traffic Measurement Collection and Reconstruction
inferred← citeshttps://doi.org/10.1109/globecom48099.2022.10001690openalex-snapshot
Accurate Communication Traffic Forecasting with Multi-Source Adaptive Feature Boosting
inferred← citeshttps://doi.org/10.1109/globecom54140.2023.10437499openalex-snapshot
AdaTeacher: Adaptive Multi-Teacher Weighting for Communication Load Forecasting
inferred← citeshttps://doi.org/10.1109/globecom54140.2023.10437579openalex-snapshot
Machine Learning for Estimating the Impact of Adding New Mobile Network Cells
inferred← citeshttps://doi.org/10.1109/glocom.2018.8647627openalex-snapshot
Feature-Selection Based Data Prioritization in Mobile Traffic Prediction Using Machine Learning
inferred← citeshttps://doi.org/10.1109/icc.2019.8761755openalex-snapshot
GANSlicing: A GAN-Based Software Defined Mobile Network Slicing Scheme for IoT Applications
inferred← citeshttps://doi.org/10.1109/icc42927.2021.9500735openalex-snapshot
Context-Aware Traffic Prediction: Loss Function Formulation for Predicting Traffic in 5G Networks
inferred← citeshttps://doi.org/10.1109/icc45041.2023.10279145openalex-snapshot
Reservation of Virtualized Resources with Optimistic Online Learning
inferred← citeshttps://doi.org/10.1109/icc45041.2023.10279534openalex-snapshot
To be Conservative or to be Aggressive? A Risk-Adaptive Mixture of Experts for Mobile Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/icc45855.2022.9838413openalex-snapshot
Data-Efficient Communication Traffic Prediction With Deep Transfer Learning
inferred← citeshttps://doi.org/10.1109/icc45855.2022.9838521openalex-snapshot
Communication Traffic Prediction with Continual Knowledge Distillation
inferred← citeshttps://doi.org/10.1109/icc45855.2022.9838982openalex-snapshot
Forecasting Busy-Hour Downlink Traffic in Cellular Networks
inferred← citeshttps://doi.org/10.1109/icc45855.2022.9839074openalex-snapshot
Cellular Traffic Prediction Using Deep Convolutional Neural Network with Attention Mechanism
inferred← citeshttps://doi.org/10.1109/iccca52192.2021.9666235openalex-snapshot
Selection of Efficient and Accurate Prediction Algorithm for Employing Real Time 5G Data Load Prediction
inferred← citeshttps://doi.org/10.1109/iccia.2019.00026openalex-snapshot
Traffic Prediction Using Attentional Spatial-Temporal Deep Learning with Accident Embedding
inferred← citeshttps://doi.org/10.1109/icct67417.2025.11374032openalex-snapshot
Spatiotemporal Prediction of Wireless Network Traffic Based on Multi-Task Deep Learning
inferred← citeshttps://doi.org/10.1109/iccworkshops53468.2022.9814643openalex-snapshot
Network Traffic Overload Prediction with Temporal Graph Attention Convolutional Networks
inferred← citeshttps://doi.org/10.1109/icdcs.2019.00095openalex-snapshot
Service Demand Prediction with Incomplete Historical Data
inferred← citeshttps://doi.org/10.1109/icdcs57875.2023.00011openalex-snapshot
ScanFed: Scalable Behavior-Based Backdoor Detection in Federated Learning
inferred← citeshttps://doi.org/10.1109/icdm65498.2025.00174openalex-snapshot
Cellular Traffic Prediction Based on Two-Stage Cross-City Transfer Learning
inferred← citeshttps://doi.org/10.1109/iceict57916.2023.10245385openalex-snapshot
ST2T: A Spatio-Temporal Transformer for Cellular Traffic Prediction in Digital Twin Systems
inferred← citeshttps://doi.org/10.1109/iciccsp53532.2022.9862437openalex-snapshot
Internet Activity Forecasting Over 5G Billing Data Using Deep Learning Techniques
inferred← citeshttps://doi.org/10.1109/icmlcn64995.2025.11140295openalex-snapshot
Uncovering Issues in the Radio Access Network by Looking at the Neighbors
inferred← citeshttps://doi.org/10.1109/icmlcn64995.2025.11140444openalex-snapshot
A Scalable DNN Training Framework for Traffic Forecasting in Mobile Networks
inferred← citeshttps://doi.org/10.1109/icnc-fskd64080.2024.10702233openalex-snapshot
Cellular Traffic Prediction Based on CVAE and Transformer
inferred← citeshttps://doi.org/10.1109/icoin63865.2025.10993156openalex-snapshot
Comparison of Network Traffic Forecasting Schemes
inferred← citeshttps://doi.org/10.1109/icosec49089.2020.9215286openalex-snapshot
Traffic Forecasting and Decision-making of Investment and Construction of Tourism Highway under the Background of Artificial Intelligence
inferred← citeshttps://doi.org/10.1109/ieeeconf60004.2024.10943047openalex-snapshot
An Adaptive Framework for Generalizing Network Traffic Prediction Towards Uncertain Environments
inferred← citeshttps://doi.org/10.1109/ijcnn48605.2020.9207655openalex-snapshot
Hybrid Prediction Model for Mobile Data Traffic: A Cluster-level Approach
inferred← citeshttps://doi.org/10.1109/ijcnn64981.2025.11228806openalex-snapshot
Cellular Network Traffic Prediction In Data-Scarce Environments: A Cross-Domain Transfer Learning Mechanism
inferred← citeshttps://doi.org/10.1109/infcomw.2019.8845178openalex-snapshot
$\alpha$-OMC: Cost-Aware Deep Learning for Mobile Network Resource Orchestration
inferred← citeshttps://doi.org/10.1109/infocom.2019.8737488openalex-snapshot
DeepCog: Cognitive Network Management in Sliced 5G Networks with Deep Learning
inferred← citeshttps://doi.org/10.1109/infocom.2019.8737493openalex-snapshot
Individual Data Plan in Virtual Network Operation: A Proactive Matching Approach
inferred← citeshttps://doi.org/10.1109/infocom48880.2022.9796918openalex-snapshot
LossLeaP: Learning to Predict for Intent-Based Networking
inferred← citeshttps://doi.org/10.1109/infocom53939.2023.10228989openalex-snapshot
Spotting Deep Neural Network Vulnerabilities in Mobile Traffic Forecasting with an Explainable AI Lens
inferred← citeshttps://doi.org/10.1109/infocom59046.2026.11571276openalex-snapshot
A First Look at Operational RAN Updates and Their Impact on Carrier Traffic Demands and Prediction
inferred← citeshttps://doi.org/10.1109/istems60181.2024.10560180openalex-snapshot
A Development of Dynamic End-To-End Slicing Network Along with the Offline SLA-Method Integrated with Deep Learning for 5G/6G Networks
inferred← citeshttps://doi.org/10.1109/istems60181.2024.10560298openalex-snapshot
An Efficient Edge Based Resource Scaling Method in Next-Generation Networks in Inntegration With Distributed NN
inferred← citeshttps://doi.org/10.1109/iwmn.2019.8804984openalex-snapshot
Multi-Service Mobile Traffic Forecasting via Convolutional Long Short-Term Memories
inferred← citeshttps://doi.org/10.1109/jiot.2023.3301019openalex-snapshot
Joint Edge Server Selection and Data Set Management for Federated-Learning-Enabled Mobile Traffic Prediction
inferred← citeshttps://doi.org/10.1109/jiot.2025.3588898openalex-snapshot
Neighboring-Satellite Beam Coordination Framework Based on Satellite Autonomous Control
inferred← citeshttps://doi.org/10.1109/jsac.2019.2904363openalex-snapshot
Deep Transfer Learning for Intelligent Cellular Traffic Prediction Based on Cross-Domain Big Data
inferred← citeshttps://doi.org/10.1109/jsac.2019.2904367openalex-snapshot
Idle Time Window Prediction in Cellular Networks with Deep Spatiotemporal Modeling
inferred← citeshttps://doi.org/10.1109/jsac.2019.2959186openalex-snapshot
Offline SLA-Constrained Deep Learning for 5G Networks Reliable and Dynamic End-to-End Slicing
inferred← citeshttps://doi.org/10.1109/jsac.2019.2959245openalex-snapshot
DeepCog: Optimizing Resource Provisioning in Network Slicing With AI-Based Capacity Forecasting
inferred← citeshttps://doi.org/10.1109/jsac.2023.3310047openalex-snapshot
Traffic Prediction-Assisted Federated Deep Reinforcement Learning for Service Migration in Digital Twins-Enabled MEC Networks
inferred← citeshttps://doi.org/10.1109/jsen.2022.3219251openalex-snapshot
MOSAL: A Subspace-Based Forecasting Algorithm for Throughput Maximization in IoT Networks
inferred← citeshttps://doi.org/10.1109/lcomm.2021.3098557openalex-snapshot
ST-Tran: Spatial-Temporal Transformer for Cellular Traffic Prediction
inferred← citeshttps://doi.org/10.1109/lcomm.2022.3141238openalex-snapshot
SDGNet: A Handover-Aware Spatiotemporal Graph Neural Network for Mobile Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/lcomm.2022.3167813openalex-snapshot
Efficient Wireless Traffic Prediction at the Edge: A Federated Meta-Learning Approach
inferred← citeshttps://doi.org/10.1109/lcomm.2023.3275327openalex-snapshot
Cellular Network Traffic Prediction Based on Correlation ConvLSTM and Self-Attention Network
inferred← citeshttps://doi.org/10.1109/lgrs.2022.3227071openalex-snapshot
Post-Stack Impedance Inversion Based on Spatio-Temporal Neural Network
inferred← citeshttps://doi.org/10.1109/main71116.2026.11622342openalex-snapshot
Event-Driven Traffic Forecasting in FTTH Networks
inferred← citeshttps://doi.org/10.1109/mascots50786.2020.9285949openalex-snapshot
Mobile Network Traffic Forecasting Using Artificial Neural Networks
inferred← citeshttps://doi.org/10.1109/mcom.001.1900601openalex-snapshot
A Machine-Learning-Based Framework for Optimizing the Operation of Future Networks
inferred← citeshttps://doi.org/10.1109/mdm.2019.00-53openalex-snapshot
STCNN: A Spatio-Temporal Convolutional Neural Network for Long-Term Traffic Prediction
inferred← citeshttps://doi.org/10.1109/meditcom49071.2021.9647571openalex-snapshot
Machine Learning for Network Slicing in Future Mobile Networks: Design and Implementation
inferred← citeshttps://doi.org/10.1109/miccis66057.2025.00052openalex-snapshot
Hybrid Attention Mechanisms for Cellular Network Traffic Prediction
inferred← citeshttps://doi.org/10.1109/mnet.001.2000047openalex-snapshot
AI-Based Autonomous Control, Management, and Orchestration in 5G: From Standards to Algorithms
inferred← citeshttps://doi.org/10.1109/mnet.011.1900437openalex-snapshot
Big Data for 5G Intelligent Network Slicing Management
inferred← citeshttps://doi.org/10.1109/nof52522.2021.9609894openalex-snapshot
A Network and Computing Resource Management Method based on Population Prediction in Mobile Networks
inferred← citeshttps://doi.org/10.1109/nof66640.2025.11223325openalex-snapshot
Enhancing Spatiotemporal Networks with xLSTM: A Scalar LSTM Approach for Cellular Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/noms56928.2023.10154215openalex-snapshot
Predicting Mobility Management Demands of Cellular Networks based on User Behavior
inferred← citeshttps://doi.org/10.1109/oecc48412.2020.9273638openalex-snapshot
Optical Network Traffic Prediction Based on Graph Convolutional Neural Networks
inferred← citeshttps://doi.org/10.1109/ojcoms.2020.3000059openalex-snapshot
Wireless Traffic Usage Forecasting Using Real Enterprise Network Data: Analysis and Methods
inferred← citeshttps://doi.org/10.1109/ojcoms.2022.3146886openalex-snapshot
Traffic Prediction-Enabled Energy-Efficient Dynamic Computing Resource Allocation in CRAN Based on Deep Learning
inferred← citeshttps://doi.org/10.1109/secon48991.2020.9158437openalex-snapshot
Cellular Network Traffic Prediction Incorporating Handover: A Graph Convolutional Approach
inferred← citeshttps://doi.org/10.1109/secon52354.2021.9491611openalex-snapshot
Traffic-Driven Sounding Reference Signal Resource Allocation in (Beyond) 5G Networks
inferred← citeshttps://doi.org/10.1109/smartnets50376.2021.9555430openalex-snapshot
Data-Driven Anomaly Detection Based on Multi-Sensor Data Fusion
inferred← citeshttps://doi.org/10.1109/tase.2024.3416952openalex-snapshot
Multi-Scenario Cellular KPI Prediction Based on Spatiotemporal Graph Neural Network
inferred← citeshttps://doi.org/10.1109/tccn.2024.3524183openalex-snapshot
Gradient Compression and Correlation Driven Federated Learning for Wireless Traffic Prediction
inferred← citeshttps://doi.org/10.1109/telfor56187.2022.9983725openalex-snapshot
Utilizing Uncertainty of Time Series Prediction in Spectrum Sharing with Radar Systems
inferred← citeshttps://doi.org/10.1109/tii.2022.3182768openalex-snapshot
Spatial-Temporal Cellular Traffic Prediction for 5G and Beyond: A Graph Neural Networks-Based Approach
inferred← citeshttps://doi.org/10.1109/tits.2019.2950416openalex-snapshot
Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting
inferred← citeshttps://doi.org/10.1109/tits.2023.3237205openalex-snapshot
Adaptive Spatiotemporal InceptionNet for Traffic Flow Forecasting
inferred← citeshttps://doi.org/10.1109/tkde.2021.3056502openalex-snapshot
Learning Dynamics and Heterogeneity of Spatial-Temporal Graph Data for Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/tmc.2018.2870135openalex-snapshot
Spatio-Temporal Analysis and Prediction of Cellular Traffic in Metropolis
inferred← citeshttps://doi.org/10.1109/tmc.2019.2917205openalex-snapshot
Max-Min Fair Resource Allocation in Millimetre-Wave Backhauls
inferred← citeshttps://doi.org/10.1109/tmc.2020.2971470openalex-snapshot
Data-Driven C-RAN Optimization Exploiting Traffic and Mobility Dynamics of Mobile Users
inferred← citeshttps://doi.org/10.1109/tmc.2020.3020582openalex-snapshot
Graph Attention Spatial-Temporal Network With Collaborative Global-Local Learning for Citywide Mobile Traffic Prediction
inferred← citeshttps://doi.org/10.1109/tmc.2021.3079117openalex-snapshot
Mobile Data Traffic Prediction by Exploiting Time-Evolving User Mobility Patterns
inferred← citeshttps://doi.org/10.1109/tmc.2021.3129796openalex-snapshot
MVSTGN: A Multi-View Spatial-Temporal Graph Network for Cellular Traffic Prediction
inferred← citeshttps://doi.org/10.1109/tmc.2022.3221773openalex-snapshot
A Unified Prediction Framework for Signal Maps: Not All Measurements are Created Equal
inferred← citeshttps://doi.org/10.1109/tmc.2022.3226448openalex-snapshot
Fine-Grained Spatio-Temporal Distribution Prediction of Mobile Content Delivery in 5G Ultra-Dense Networks
inferred← citeshttps://doi.org/10.1109/tmc.2023.3325301openalex-snapshot
Bayesian Meta-Learning for Adaptive Traffic Prediction in Wireless Networks
inferred← citeshttps://doi.org/10.1109/tmc.2023.3332034openalex-snapshot
Location Leakage in Federated Signal Maps
inferred← citeshttps://doi.org/10.1109/tmc.2025.3531544openalex-snapshot
DeExp: Revealing Model Vulnerabilities for Spatio-Temporal Mobile Traffic Forecasting With Explainable AI
inferred← citeshttps://doi.org/10.1109/tmc.2025.3538871openalex-snapshot
Burst-Sensitive Traffic Forecast via Multi-Property Personalized Fusion in Federated Learning
inferred← citeshttps://doi.org/10.1109/tmc.2026.3684577openalex-snapshot
MobileLLM: Semantic-Enhanced Large Language Model for Multimodal Cellular Traffic Prediction in Urban Networks
inferred← citeshttps://doi.org/10.1109/tmlcn.2024.3420268openalex-snapshot
Sample-Efficient Multi-Agent DQNs for Scalable Multi-Domain 5G+ Inter-Slice Orchestration
inferred← citeshttps://doi.org/10.1109/tnet.2021.3053771openalex-snapshot
Deep Reinforcement Learning With Spatio-Temporal Traffic Forecasting for Data-Driven Base Station Sleep Control
inferred← citeshttps://doi.org/10.1109/tnet.2021.3136707openalex-snapshot
Deep Transfer Learning Across Cities for Mobile Traffic Prediction
inferred← citeshttps://doi.org/10.1109/tnet.2021.3137084openalex-snapshot
Adversarial Attacks Against Deep Learning-Based Network Intrusion Detection Systems and Defense Mechanisms
inferred← citeshttps://doi.org/10.1109/tnet.2023.3268982openalex-snapshot
Graph-Tensor Neural Networks for Network Traffic Data Imputation
inferred← citeshttps://doi.org/10.1109/tnet.2023.3285812openalex-snapshot
TrafAda: Cost-Aware Traffic Adaptation for Maximizing Bitrates in Live Streaming
inferred← citeshttps://doi.org/10.1109/tnnls.2022.3183903openalex-snapshot
Bidirectional Spatial-Temporal Adaptive Transformer for Urban Traffic Flow Forecasting
inferred← citeshttps://doi.org/10.1109/tnse.2020.3031347openalex-snapshot
Leveraging Multiplexing Gain in Network Slice Bundles
inferred← citeshttps://doi.org/10.1109/tnse.2025.3629133openalex-snapshot
A Spatial-Temporal Graph Convolutional Network With Self-Attention for City-Level Cellular Network Traffic Prediction
inferred← citeshttps://doi.org/10.1109/tnsm.2020.3032829openalex-snapshot
ARENA: A Data-Driven Radio Access Networks Analysis of Football Events
inferred← citeshttps://doi.org/10.1109/tnsm.2022.3187251openalex-snapshot
Cellular Traffic Prediction: A Deep Learning Method Considering Dynamic Nonlocal Spatial Correlation, Self-Attention, and Correlation of Spatiotemporal Feature Fusion
inferred← citeshttps://doi.org/10.1109/tnsm.2022.3214483openalex-snapshot
Citywide Mobile Traffic Forecasting Using Spatial-Temporal Downsampling Transformer Neural Networks
inferred← citeshttps://doi.org/10.1109/tnsm.2024.3377442openalex-snapshot
Explainable and Transferable Loss Meta-Learning for Zero-Touch Anticipatory Network Management
inferred← citeshttps://doi.org/10.1109/tnsm.2025.3563978openalex-snapshot
ETCN-NNC-LB: Ensemble TCNs With L-BFGS-B Optimized No Negative Constraint-Based Forecasting for Network Traffic
inferred← citeshttps://doi.org/10.1109/tnsm.2025.3582533openalex-snapshot
A Two-Step Cellular Network Traffic Forecasting Method Integrating Decomposition and Deep Neural Networks Based on Bayesian Joint Parameter Optimization
inferred← citeshttps://doi.org/10.1109/tnsm.2025.3595919openalex-snapshot
Long-Term Traffic Flow Prediction: A Knowledge-Driven Graph Attention Spatio-Temporal Network
inferred← citeshttps://doi.org/10.1109/tnsm.2025.3628788openalex-snapshot
The TES Framework: Joint Statistical Modeling and Machine Learning for Network KPI Forecasting
inferred← citeshttps://doi.org/10.1109/ton.2025.3542456openalex-snapshot
Bridging Cross-Layer Interactions Between 5G RAN and MEC for Latency-Critical Video Analytics
inferred← citeshttps://doi.org/10.1109/tpds.2023.3245092openalex-snapshot
Large-Scale Measurements and Prediction of DC-WAN Traffic
inferred← citeshttps://doi.org/10.1109/tsp.2019.8769088openalex-snapshot
Adaptive Resource Scheduling based on Neural Network and Mobile Traffic Prediction
inferred← citeshttps://doi.org/10.1109/tsusc.2024.3504242openalex-snapshot
Federated Learning in Mobile Networks: A Comprehensive Case Study on Traffic Forecasting
inferred← citeshttps://doi.org/10.1109/tsusc.2025.3620441openalex-snapshot
EMC-LSP: A Novel Lightweight Architecture for Edge Multi-Node Long Sequence Prediction
inferred← citeshttps://doi.org/10.1109/tvt.2020.3005724openalex-snapshot
Multi-Task Learning at the Mobile Edge: An Effective Way to Combine Traffic Classification and Prediction
showing the first 200 of 268
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.