Mobile Virtual Reality Rail Traffic Congestion Prediction Algorithm Based on Convolutional Neural Network

Mobile Virtual Reality Rail Traffic Congestion Prediction Algorithm Based on Convolutional Neural Network

In order to explore a mobile virtual reality railway traffic congestion prediction algorithm based on convolutional neural network, an expanded causal convolution neural network (DCFCN) was proposed, which introduced the expanded convolution to increase the size of the receptive field and obtain the...

Full description

Bibliographic Details
Main Authors:	Li, Y. (Author), Wang, Y. (Author)
Format:	Article
Language:	English
Published:	Hindawi Limited 2022
Subjects:	Causal convolutions Computational efficiency Congestion prediction Convolution Convolution neural network Convolutional neural network Convolutional neural networks Double layers Forecasting Long short-term memory Prediction algorithms Rail traffic Railroad transportation Railway traffic Receptive fields Single layer Traffic congestion Virtual reality
Online Access:	View Fulltext in Publisher

Similar Items

Large-Scale Road Network Congestion Pattern Analysis and Prediction Using Deep Convolutional Autoencoder
by: Navin Ranjan, et al.
Published: (2021-05-01)

A Hybrid Deep Convolutional Neural Network Approach for Predicting the Traffic Congestion Index
by: Duy Tran Quang, et al.
Published: (2021-05-01)

City-Wide Traffic Congestion Prediction Based on CNN, LSTM and Transpose CNN
by: Navin Ranjan, et al.
Published: (2020-01-01)

Interactive Temporal Recurrent Convolution Network for Traffic Prediction in Data Centers
by: Xiaofeng Cao, et al.
Published: (2018-01-01)

EFFECT OF VARIOUS DIMENSION CONVOLUTIONAL LAYER FILTERS ON TRAFFIC SIGN CLASSIFICATION ACCURACY
by: V. N. Sichkar, et al.
Published: (2019-01-01)

Appropriateness of Numbers of Receptive Fields in Convolutional Neural Networks Based on Classifying CIFAR-10 and EEACL26 Datasets
by: Romanuke Vadim
Published: (2018-12-01)

A Novel Fuzzy-Based Convolutional Neural Network Method to Traffic Flow Prediction With Uncertain Traffic Accident Information
by: Jiyao An, et al.
Published: (2019-01-01)

Transferability of a Convolutional Neural Network (CNN) to Measure Traffic Density
by: Jiyong Chung, et al.
Published: (2021-05-01)

Traffic Accident’s Severity Prediction: A Deep-Learning Approach-Based CNN Network
by: Ming Zheng, et al.
Published: (2019-01-01)

Network Traffic Classifier With Convolutional and Recurrent Neural Networks for Internet of Things
by: Manuel Lopez-Martin, et al.
Published: (2017-01-01)

Detection of Safe Passage for Trains at Rail Level Crossings Using Deep Learning
by: Teresa Pamuła, et al.
Published: (2021-09-01)

Deep Convolutional Neural Networks: Structure, Feature Extraction and Training
by: Namatēvs Ivars
Published: (2017-12-01)

Graph Neural Network for Traffic Flow Situation Prediction
by: JIANG Shan, DING Zhiming, XU Xinrun, YAN Jin
Published: (2021-06-01)

Classification of Traffic Signs: The European Dataset
by: Citlalli Gamez Serna, et al.
Published: (2018-01-01)

Learning Traffic as Images: A Deep Convolutional Neural Network for Large-Scale Transportation Network Speed Prediction
by: Xiaolei Ma, et al.
Published: (2017-04-01)

Spatio-Temporal Traffic Flow Prediction in Madrid: An Application of Residual Convolutional Neural Networks
by: Daniel Vélez-Serrano, et al.
Published: (2021-05-01)

Spatiotemporal Recurrent Convolutional Networks for Traffic Prediction in Transportation Networks
by: Haiyang Yu, et al.
Published: (2017-06-01)

Inter-Patient Congestive Heart Failure Detection Using ECG-Convolution-Vision Transformer Network
by: Huang, J., et al.
Published: (2022)

Traffic sign recognition algorithm based on improved convolution neural network
by: ZHU Yongjia, et al.
Published: (2018-10-01)

Data Transformation Schemes for CNN-Based Network Traffic Analysis: A Survey
by: Jacek Krupski, et al.
Published: (2021-08-01)

An attempt of finding an appropriate number of convolutional layers in cnns based on benchmarks of heterogeneous datasets
by: Romanuke Vadim V.
Published: (2018-07-01)

TOWARDS AN EFFICIENT TRAFFIC CONGESTION PREDICTION METHOD BASED ON NEURAL NETWORKS AND BIG GPS DATA
by: Wiam Elleuch, et al.
Published: (2019-06-01)

Airborne Network Traffic Identification Method under Small Training Samples
Published: (2020-10-01)

Efficient Traffic Accident Warning Based on Unsupervised Prediction Framework
by: Yun-Feng Zhou, et al.
Published: (2021-01-01)

Encrypted Network Traffic Classification Using Deep and Parallel Network-in-Network Models
by: Zhiyong Bu, et al.
Published: (2020-01-01)

A Fusion Approach to Detect Traffic Signs Using Registered Color Images and Noisy Airborne LiDAR Data
by: Mohammadreza Javanmardi, et al.
Published: (2021-12-01)

Global Spatial-Temporal Graph Convolutional Network for Urban Traffic Speed Prediction
by: Liang Ge, et al.
Published: (2020-02-01)

Spatio-Temporal Network Traffic Estimation and Anomaly Detection Based on Convolutional Neural Network in Vehicular Ad-Hoc Networks
by: Laisen Nie, et al.
Published: (2018-01-01)

Appropriate Number of Standard 2 × 2 Max Pooling Layers and Their Allocation in Convolutional Neural Networks for Diverse and Heterogeneous Datasets
by: Romanuke Vadim V.
Published: (2017-12-01)

Research on Traffic Speed Prediction by Temporal Clustering Analysis and Convolutional Neural Network With Deformable Kernels (May, 2018)
by: Guojiang Shen, et al.
Published: (2018-01-01)

Intelligent deep fusion network for urban traffic flow anomaly identification
by: Belhadi, A., et al.
Published: (2022)

Efficient Rail Area Detection Using Convolutional Neural Network
by: Zhangyu Wang, et al.
Published: (2018-01-01)

A Novel Spatio-Temporal Model for City-Scale Traffic Speed Prediction
by: Kun Niu, et al.
Published: (2019-01-01)

LdsConv: Learned Depthwise Separable Convolutions by Group Pruning
by: Wenxiang Lin, et al.
Published: (2020-08-01)

The Importance of Loss Functions for Increasing the Generalization Abilities of a Deep Learning-Based next Frame Prediction Model for Traffic Scenes
by: Sandra Aigner, et al.
Published: (2020-04-01)

Traffic Data Imputation Using Deep Convolutional Neural Networks
by: Ouafa Benkraouda, et al.
Published: (2020-01-01)

Customer Prediction using Parking Logs with Recurrent Neural Networks
by: Liaq Mudassar, et al.
Published: (2018-07-01)

Long-Range Dependent Traffic Classification with Convolutional Neural Networks Based on Hurst Exponent Analysis
by: Katarzyna Filus, et al.
Published: (2020-10-01)

Spatiotemporal Data Fusion in Graph Convolutional Networks for Traffic Prediction
by: Baoxin Zhao, et al.
Published: (2020-01-01)

Invariance and Same-Equivariance Measures for Convolutional Neural Networks
by: Facundo Quiroga, et al.
Published: (2020-05-01)