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A Deep-Learning Model for Estimating the Impact of Social Events on Traffic Demand on a Cell Basis

https://doi.org/10.1109/access.2021.3078113

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What this work says

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

inferredcites →https://doi.org/10.1002/(sici)1097-4571(199701)48:1<88::aid-asi10>3.0.co;2-#openalex-snapshot

Backpropagation: Theory, architectures, and applications

inferredcites →https://doi.org/10.1002/9781119954224openalex-snapshot

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inferredcites →https://doi.org/10.1002/ett.2583openalex-snapshot

Energy savings scheme in radio access networks via compressive sensing‐based traffic load prediction

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Traffic Modeling and Prediction using ARIMA/GARCH Model

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Cellular Traffic Prediction and Classification: A Comparative Evaluation of LSTM and ARIMA

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Convolutional neural networks: an overview and application in radiology

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Neural networks: A comprehensive foundation

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EEG-based user identification system using 1D-convolutional long short-term memory neural networks

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Auto-encoder based dimensionality reduction

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Wireless Traffic Modeling and Prediction Using Seasonal ARIMA Models

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A Context-Aware Data-Driven Algorithm for Small Cell Site Selection in Cellular Networks

inferredcites →https://doi.org/10.1109/chinasip.2015.7230444openalex-snapshot

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Deep Learning in Mobile and Wireless Networking: A Survey

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A Comparison of Machine and Statistical Time Series Learning for Encrypted Traffic Prediction

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Network Traffic Prediction and Result Analysis Based on Seasonal ARIMA and Correlation Coefficient

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Mobile Demand Forecasting via Deep Graph-Sequence Spatiotemporal Modeling in Cellular Networks

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DeepCog: Optimizing Resource Provisioning in Network Slicing With AI-Based Capacity Forecasting

inferredcites →https://doi.org/10.1109/lcomm.2018.2841832openalex-snapshot

Citywide Cellular Traffic Prediction Based on Densely Connected Convolutional Neural Networks

inferredcites →https://doi.org/10.1109/lwc.2016.2561924openalex-snapshot

Estimating Mobile Traffic Demand Using Twitter

inferredcites →https://doi.org/10.1109/lwc.2018.2795605openalex-snapshot

Spatio-Temporal Wireless Traffic Prediction With Recurrent Neural Network

inferredcites →https://doi.org/10.1109/mcom.2015.7010548openalex-snapshot

Management architecture for location-aware self-organizing LTE/LTE-a small cell networks

inferredcites →https://doi.org/10.1109/mcom.2018.1700580openalex-snapshot

Applying Social Event Data for the Management of Cellular Networks

inferredcites →https://doi.org/10.1109/mdm48529.2020.00057openalex-snapshot

A Big Data Platform For Spatio-Temporal Social Event Discovery

inferredcites →https://doi.org/10.1109/mnet.2014.6963801openalex-snapshot

Challenges in 5G: how to empower SON with big data for enabling 5G

inferredcites →https://doi.org/10.1109/mnet.2018.1800127openalex-snapshot

DeepTP: An End-to-End Neural Network for Mobile Cellular Traffic Prediction

inferredcites →https://doi.org/10.1109/mprv.2007.53openalex-snapshot

Cellular Census: Explorations in Urban Data Collection

inferredcites →https://doi.org/10.1109/mvt.2015.2431753openalex-snapshot

Context-Aware Self-Optimization: Evolution Based on the Use Case of Load Balancing in Small-Cell Networks

inferredcites →https://doi.org/10.1109/mvt.2015.2479657openalex-snapshot

Context-Aware Self-Healing: User Equipment as the Main Source of Information for Small-Cell Indoor Networks

inferredcites →https://doi.org/10.1109/mwc.2017.1600304wcopenalex-snapshot

Intelligent 5G: When Cellular Networks Meet Artificial Intelligence

inferredcites →https://doi.org/10.1109/pimrc.1997.627037openalex-snapshot

A dynamic individualized location management algorithm

inferredcites →https://doi.org/10.1109/pimrc.2017.8292737openalex-snapshot

A study of deep learning networks on mobile traffic forecasting

inferredcites →https://doi.org/10.1109/pimrc.2018.8581000openalex-snapshot

Mobile Traffic Prediction from Raw Data Using LSTM Networks

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/surv.2012.040912.00180openalex-snapshot

A Survey on Context-Aware Mobile and Wireless Networking: On Networking and Computing Environments' Integration

inferredcites →https://doi.org/10.1109/tits.2017.2695438openalex-snapshot

A Generative Model of Urban Activities from Cellular Data

inferredcites →https://doi.org/10.1109/tits.2019.2909571openalex-snapshot

Short-Term Prediction of Passenger Demand in Multi-Zone Level: Temporal Convolutional Neural Network With Multi-Task Learning

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Exploiting the Dynamic Mutual Influence for Predicting Social Event Participation

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Identifying On-Site Users for Social Events: Mobility, Content, and Social Relationship

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Spatio-Temporal Analysis and Prediction of Cellular Traffic in Metropolis

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Big Data Driven Mobile Traffic Understanding and Forecasting: A Time Series Approach

inferredcites →https://doi.org/10.1109/tvt.2013.2247431openalex-snapshot

Automatic Replanning of Tracking Areas in Cellular Networks

inferredcites →https://doi.org/10.1109/vetecf.1999.797068openalex-snapshot

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inferredcites →https://doi.org/10.1109/vtcfall.2018.8690851openalex-snapshot

Traffic Prediction Based on Random Connectivity in Deep Learning with Long Short-Term Memory

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Network Traffic Prediction Based on Deep Belief Network in Wireless Mesh Backbone Networks

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Twitter as a Source for Spatial Traffic Information in Big Data-Enabled Self-Organizing Networks

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PBN

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Understanding Mobile Traffic Patterns of Large Scale Cellular Towers in Urban Environment

inferredcites →https://doi.org/10.1145/3209582.3209606openalex-snapshot

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

inferredcites →https://doi.org/10.1145/507338.507355openalex-snapshot

Data mining

inferredcites →https://doi.org/10.1155/2013/165146openalex-snapshot

Survey and Challenges of QoE Management Issues in Wireless Networks

inferredcites →https://doi.org/10.1155/2018/3479246openalex-snapshot

A Geometric Method for Estimating the Nominal Cell Range in Cellular Networks

inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-snapshot

Long Short-Term Memory

inferredcites →https://doi.org/10.2307/1267710openalex-snapshot

Time Series Analysis: Forecasting and Control

inferredcites →https://doi.org/10.2307/3150485openalex-snapshot

Time Series Analysis: Forecasting and Control

inferredcites →https://doi.org/10.3390/s16101563openalex-snapshot

Indoor-Outdoor Detection Using a Smart Phone Sensor

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Exploiting Generative AI to Scale up Intelligent Tutoring Systems

inferredcites →https://doi.org/10.4324/9780203763247openalex-snapshot

Backpropagation

inferredcites →https://doi.org/10.48550/arxiv.1502.02127openalex-snapshot

Hyperparameter Search in Machine Learning

inferredcites →https://doi.org/10.5121/ijmnct.2013.3603openalex-snapshot

Short-Term Traffic Volume Prediction in UMTS Networks using the Kalman Filter Algorithm

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Big Data Empowered Self Organized Networks

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Attention Is All You Need

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inferred← citeshttps://doi.org/10.1109/compsac61105.2024.00353openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/fmec59375.2023.10306017openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/globecom48099.2022.10001059openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/ictc66702.2025.11388611openalex-snapshot

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inferred← citeshttps://doi.org/10.1109/iicspi66775.2025.11437891openalex-snapshot

Research on 5G Traffic Prediction Method Based on VMD-XGBoost and Bootstrap

inferred← citeshttps://doi.org/10.1109/tnsm.2023.3249470openalex-snapshot

Forecasting Framework for Mobile Networks Based on Automatic Feature Selection

inferred← citeshttps://doi.org/10.1109/tnsm.2025.3595919openalex-snapshot

Long-Term Traffic Flow Prediction: A Knowledge-Driven Graph Attention Spatio-Temporal Network

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Dual-Scale Cellular Traffic Prediction Based on FastDTW for Graph Neural Network

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inferred← citeshttps://doi.org/10.33168/jsms.2022.0205openalex-snapshot

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inferred← citeshttps://doi.org/10.3390/make8090260openalex-snapshot

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