Cover Image

Overcoming Data Limitations in Internet Traffic Forecasting: LSTM Models with Transfer Learning and Wavelet Augmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Saha, Sajal, Haque, Anwar, Sidebottom, Greg
Format:	Preprint
Published:	2024
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Intelligent Routing Algorithm over SDN: Reusable Reinforcement Learning Approach
by: Wumian, Wang, et al.
Published: (2024)

An Adaptive End-to-End IoT Security Framework Using Explainable AI and LLMs
by: Baral, Sudipto, et al.
Published: (2024)

ConvLSTMTransNet: A Hybrid Deep Learning Approach for Internet Traffic Telemetry
by: Saha, Sajal, et al.
Published: (2024)

Wavelet-Inspired Multiscale Graph Convolutional Recurrent Network for Traffic Forecasting
by: Qian, Qipeng, et al.
Published: (2024)

How does the Performance of the Data-driven Traffic Flow Forecasting Models deteriorate with Increasing Forecasting Horizon? An Extensive Approach Considering Statistical, Machine Learning and Deep Learning Models
by: Sherfenaz, Amanta, et al.
Published: (2025)

Enhancing Spatiotemporal Networks with xLSTM: A Scalar LSTM Approach for Cellular Traffic Forecasting
by: Ali, Khalid, et al.
Published: (2025)

Enhancing Encrypted Internet Traffic Classification Through Advanced Data Augmentation Techniques
by: Zion, Yehonatan, et al.
Published: (2024)

Cross-household Transfer Learning Approach with LSTM-based Demand Forecasting
by: Rahal, Manal, et al.
Published: (2026)

Network Level Spatial Temporal Traffic State Forecasting with Hierarchical-Attention-LSTM (HierAttnLSTM)
by: Zhang, Tianya
Published: (2022)

Quantile LSTM: A Robust LSTM for Anomaly Detection In Time Series Data
by: Saha, Snehanshu, et al.
Published: (2023)

An Ensembled Penalized Federated Learning Framework for Falling People Detection
by: Rao, Sizhe, et al.
Published: (2025)

Spatiotemporal Forecasting of Traffic Flow using Wavelet-based Temporal Attention
by: Jakhmola, Yash, et al.
Published: (2024)

Graph-Augmented LSTM for Forecasting Sparse Anomalies in Graph-Structured Time Series
by: Pillai, Sneh
Published: (2025)

Short-Term Electricity Demand Forecasting of Dhaka City Using CNN with Stacked BiLSTM
by: Akhter, Kazi Fuad Bin, et al.
Published: (2024)

BiLSTM-VHP: BiLSTM-Powered Network for Viral Host Prediction
by: Efat, Azher Ahmed, et al.
Published: (2025)

Online Data Augmentation for Forecasting with Deep Learning
by: Cerqueira, Vitor, et al.
Published: (2024)

SSMT: Few-Shot Traffic Forecasting with Single Source Meta-Transfer
by: Bhaumik, Kishor Kumar, et al.
Published: (2024)

Wave-Mask/Mix: Exploring Wavelet-Based Augmentations for Time Series Forecasting
by: Arabi, Dona, et al.
Published: (2024)

HMM-LSTM Fusion Model for Economic Forecasting
by: Sivakumar, Guhan
Published: (2025)

WEST GCN-LSTM: Weighted Stacked Spatio-Temporal Graph Neural Networks for Regional Traffic Forecasting
by: Theodoropoulos, Theodoros, et al.
Published: (2024)

Addressing Data Heterogeneity in Federated Learning of Cox Proportional Hazards Models
by: Seidi, Navid, et al.
Published: (2024)

Data Augmentation for Traffic Classification
by: Wang, Chao, et al.
Published: (2024)

Efficient Prompt Learning for Traffic Forecasting
by: Zhang, Qianru, et al.
Published: (2026)

Meta-learning and Data Augmentation for Stress Testing Forecasting Models
by: Inácio, Ricardo, et al.
Published: (2024)

Hybrid SARIMA LSTM Model for Local Weather Forecasting: A Residual Learning Approach for Data Driven Meteorological Prediction
by: Rajeev, Shreyas, et al.
Published: (2026)

FUSE-Traffic: Fusion of Unstructured and Structured Data for Event-aware Traffic Forecasting
by: Yu, Chenyang, et al.
Published: (2025)

LISA: Learning-Integrated Space Partitioning Framework for Traffic Accident Forecasting on Heterogeneous Spatiotemporal Data
by: An, Bang, et al.
Published: (2024)

Overcoming the Modality Gap in Context-Aided Forecasting
by: Zheng, Vincent Zhihao, et al.
Published: (2026)

SoK: Privacy-aware LLM in Healthcare: Threat Model, Privacy Techniques, Challenges and Recommendations
by: Tahera, Mohoshin Ara, et al.
Published: (2026)

WDformer: A Wavelet-based Differential Transformer Model for Time Series Forecasting
by: Wang, Xiaojian, et al.
Published: (2025)

Enhancing Wildfire Forecasting Through Multisource Spatio-Temporal Data, Deep Learning, Ensemble Models and Transfer Learning
by: Jadouli, Ayoub, et al.
Published: (2024)

EmoAugNet: A Signal-Augmented Hybrid CNN-LSTM Framework for Speech Emotion Recognition
by: Paul, Durjoy Chandra, et al.
Published: (2025)

Weakly-Supervised Anomaly Detection in Surveillance Videos Based on Two-Stream I3D Convolution Network
by: Nejad, Sareh Soltani, et al.
Published: (2024)

Temporal Graph Learning Recurrent Neural Network for Traffic Forecasting
by: Lee, Sanghyun, et al.
Published: (2024)

Forecasting NCAA Basketball Outcomes with Deep Learning: A Comparative Study of LSTM and Transformer Models
by: Habib, Md Imtiaz
Published: (2025)

Overcoming Brittleness in Pareto-Optimal Learning-Augmented Algorithms
by: Angelopoulos, Spyros, et al.
Published: (2024)

Studying the Role of Synthetic Data for Machine Learning-based Wireless Networks Traffic Forecasting
by: Pulido, José, et al.
Published: (2026)

Traffic Flow Reconstruction from Limited Collected Data
by: Baloul, Nail, et al.
Published: (2026)

Using the SEKF to Transfer NN Models of Dynamical Systems with Limited Data
by: Hammond, Joshua E., et al.
Published: (2026)

Unlocking the Power of LSTM for Long Term Time Series Forecasting
by: Kong, Yaxuan, et al.
Published: (2024)