Passenger demand forecasting in scheduled transportation
N Banerjee, A Morton, K Akartunalı - European Journal of Operational …, 2020 - Elsevier
The aim of this review article is to provide a synoptic and critical evaluation of the extensive
research that has been performed in demand forecasting in the scheduled passenger …
research that has been performed in demand forecasting in the scheduled passenger …
Potential energy conservation and CO2 emissions reduction related to China's road transportation
As the largest mode in China's transportation industry, road transportation is the vital part to
achieve a goal of congestion and emissions reduction. We analyzed the future development …
achieve a goal of congestion and emissions reduction. We analyzed the future development …
Optimizing the artificial neural network parameters using a biased random key genetic algorithm for time series forecasting
Abstract Artificial Neural Networks (ANN) is one of the most used methods in time series
forecasting. Mostly, it is hard to determine the design and weight parameters of ANNs by …
forecasting. Mostly, it is hard to determine the design and weight parameters of ANNs by …
Cluster-based LSTM network for short-term passenger flow forecasting in urban rail transit
Short-term passenger flow forecasting is an essential component for the operation of urban
rail transit (URT). Therefore, it is necessary to obtain a higher prediction precision with the …
rail transit (URT). Therefore, it is necessary to obtain a higher prediction precision with the …
A multi-pattern deep fusion model for short-term bus passenger flow forecasting
Short-term passenger flow forecasting is one of the crucial components in transportation
systems with data support for transportation planning and management. For forecasting bus …
systems with data support for transportation planning and management. For forecasting bus …
Multi-point short-term prediction of station passenger flow based on temporal multi-graph convolutional network
Y Wang, Y Qin, J Guo, Z Cao, L Jia - Physica A: Statistical Mechanics and …, 2022 - Elsevier
Prediction of passenger flow distribution in urban rail transit stations can provide important
data support for passenger flow organization and passenger travel guidance. However …
data support for passenger flow organization and passenger travel guidance. However …
Container flow forecasting through neural networks based on metaheuristics
In this paper we propose a fuzzy neural network prediction approach based on
metaheuristics for container flow forecasting. The approach uses fuzzy if–then rules for …
metaheuristics for container flow forecasting. The approach uses fuzzy if–then rules for …
Sustainability of railway undertaking services with lean philosophy in risk management—Case study
The sustainability of services in undertakings which operate in railway passenger transport
is closely connected with efforts to provide high-quality and time-acceptable services to the …
is closely connected with efforts to provide high-quality and time-acceptable services to the …
High-speed railway express delivery volume forecast based on data-driven ensemble forecast approaches: The China case
W Huang, Y Yin, H Li, A Xie, Y Fan - Expert Systems with Applications, 2024 - Elsevier
Current researches on logistics delivery volume forecast mainly focus on traditional
transportation modes such as road, railway, and aviation, with little research on predicting …
transportation modes such as road, railway, and aviation, with little research on predicting …
Public Transit Demand Prediction During Highly Dynamic Conditions: A Meta-Analysis of State-of-the-Art Models and Open-Source Benchmarking Infrastructure
Real-time demand prediction is a critical input for dynamic bus routing. While many
researchers have developed numerous complex methods to predict short-term transit …
researchers have developed numerous complex methods to predict short-term transit …