Traffic flow prediction models–A review of deep learning techniques

AA Kashyap, S Raviraj, A Devarakonda… - Cogent …, 2022 - Taylor & Francis
Traffic flow prediction is an essential part of the intelligent transport system. This is the
accurate estimation of traffic flow in a given region at a particular interval of time in the future …

RETRACTED ARTICLE: An automated exploring and learning model for data prediction using balanced CA-SVM

S Neelakandan, D Paulraj - Journal of Ambient Intelligence and …, 2021 - Springer
The rainfall prediction is important for metrological department as it closely associated with
our environment and human life. An accuracy of rainfall prediction has great important for …

Predicting electric vehicle charging demand using a heterogeneous spatio-temporal graph convolutional network

S Wang, A Chen, P Wang, C Zhuge - Transportation Research Part C …, 2023 - Elsevier
Abstract Short-term Electric Vehicle (EV) charging demand prediction is an essential task in
the fields of smart grid and intelligent transportation systems, as understanding the …

Investigating spatio-temporal mobility patterns and changes in metro usage under the impact of COVID-19 using Taipei Metro smart card data

CM Mützel, J Scheiner - Public Transport, 2022 - Springer
Modern public transit systems are often run with automated fare collection (AFC) systems in
combination with smart cards. These systems passively collect massive amounts of detailed …

[PDF][PDF] Suggestion Mining from Opinionated Text of Big Social Media Data.

Y Alotaibi, MN Malik, HH Khan, A Batool… - … , Materials & Continua, 2021 - researchgate.net
Social media data are rapidly increasing and constitute a source of user opinions and tips
on a wide range of products and services. The increasing availability of such big data on …

Progress prediction of Parkinson's disease based on graph wavelet transform and attention weighted random forest

Z Xue, T Zhang, L Lin - Expert systems with applications, 2022 - Elsevier
The progress prediction of Parkinson's disease (PD) is one of the most important issues in
early diagnosis of PD. Many researches have been conducted in this field, however, most …

Passenger flow prediction using smart card data from connected bus system based on interpretable xgboost

L Zou, S Shu, X Lin, K Lin, J Zhu… - … and Mobile Computing, 2022 - Wiley Online Library
Bus passenger flow prediction is a critical component of advanced transportation information
system for public traffic management, control, and dispatch. With the development of artificial …

Forecasting metro rail transit passenger flow with multiple-attention deep neural networks and surrounding vehicle detection devices

JL Wu, M Lu, CY Wang - Applied Intelligence, 2023 - Springer
In the rapid development of public transportation led, the traffic flow prediction has become
one of the most crucial issues, especially estimating the number of passengers using the …

Predicting irregularities in arrival times for transit buses with recurrent neural networks using GPS coordinates and weather data

O Alam, A Kush, A Emami, P Pouladzadeh - Journal of Ambient …, 2021 - Springer
Intelligent transportation systems (ITS) play an important role in the quality of life of citizens
in any metropolitan city. Despite various policies and strategies incorporated to increase the …

Impacts of weather on short-term metro passenger flow forecasting using a deep LSTM neural network

L Liu, RC Chen, S Zhu - Applied Sciences, 2020 - mdpi.com
Metro systems play a key role in meeting urban transport demands in large cities. The close
relationship between historical weather conditions and the corresponding passenger flow …