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SSGRU: A novel hybrid stacked GRU-based traffic volume prediction approach in a road network
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Deep learning for short-term traffic flow prediction
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Is Combining Classifiers with Stacking Better than Selecting the Best One?
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A Hybrid Stacked Traffic Volume Prediction Approach for a Sparse Road Network
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Short-term traffic flow prediction with LSTM recurrent neural network
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Short-time traffic flow prediction with ARIMA-GARCH model
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Machine Learning-Based Models for Real-time Traffic Flow Prediction in Vehicular Networks
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Automated Attack and Defense Framework toward 5G Security
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Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting
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LSTM: A Search Space Odyssey
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TVDR: A Novel Traffic Volume Aware Data Routing Protocol for Vehicular Networks
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A reactive solution with a redundancy-based error correction mechanism for video dissemination over vehicular ad hoc networks
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Traffic aware video dissemination over vehicular ad hoc networks
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Accuracy Analysis of Short-term Traffic Flow Prediction Models for Vehicular Clouds
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Does the Spatial Weight Configuration Matter in the Determination of the Effects of Environmental Externalities on Housing Prices?
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Long short-term memory recurrent neural network architectures for large scale acoustic modeling
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AN OVERVIEW OF POPULAR DEEP LEARNING METHODS
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Forecasting Traffic Flow Conditions in an Urban Network: Comparison of Multivariate and Univariate Approaches
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LSTM-based Deep Learning Models for Non-factoid Answer Selection
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Stacked Convolutional and Recurrent Neural Networks for Music Emotion Recognition
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Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
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Root mean square error (RMSE) or mean absolute error (MAE)? – Arguments against avoiding RMSE in the literature
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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A Spatiotemporal Locomotive Axle Temperature Prediction Approach Based on Ensemble Graph Convolutional Recurrent Unit Networks
inferred← citeshttps://doi.org/10.3390/s23020841openalex-snapshot
MD-GCN: A Multi-Scale Temporal Dual Graph Convolution Network for Traffic Flow Prediction
inferred← citeshttps://doi.org/10.3390/s25216602openalex-snapshot
Ship Motion Attitude Prediction Model Based on FMD-IBKA-BTGN
inferred← citeshttps://doi.org/10.4018/979-8-3693-1301-5.ch006openalex-snapshot
Dynamic Intelligence-Driven Engineering Flooding Attack Prediction Using Ensemble Learning
inferred← citeshttps://doi.org/10.4271/2025-99-0009openalex-snapshot
The Traffic Light Control Strategy at Intersections in Intelligent Transportation Systems
inferred← citeshttps://doi.org/10.7717/peerj-cs.1011openalex-snapshot
A GRU-based traffic situation prediction method in multi-domain software defined network
inferred← citeshttps://doi.org/10.7717/peerj-cs.1484openalex-snapshot
Spatio-temporal causal graph attention network for traffic flow prediction in intelligent transportation systems
inferred← citeshttps://doi.org/10.7717/peerj-cs.3224openalex-snapshot
Enhanced congestion prediction of traffic flow using a hybrid attention-based deep learning model
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