A review of demand forecasting models and methodological developments within tourism and passenger transportation industry

I Ghalehkhondabi, E Ardjmand, WA Young… - Journal of Tourism …, 2019 - emerald.com
Purpose The purpose of this paper is to review the current literature in the field of tourism
demand forecasting. Design/methodology/approach Published papers in the high quality …

Prediction of rural travel demand by spatial regression and artificial neural network methods (Tabriz County)

M Aghayari Hir, M Zaheri, N Rahimzadeh - Journal of transportation …, 2023 - safetylit.org
Understanding of the current travel pattern is necessary for identifying and analyzing traffic
problems, the movement of people and for developing travel forecasting and prediction …

Air cargo transport demand forecasting using ConvLSTM2D, an artificial neural network architecture approach

JGM Anguita, OD Olariaga - Case Studies on Transport Policy, 2023 - Elsevier
The prediction of air traffic demand (passengers and cargo) in a regional/national air
transport system is essential. Knowing the behavior of future demand helps, on the one …

The influence of service quality on user's perceived satisfaction with light rail transit service in Klang Valley, Malaysia

ANH Ibrahim, MN Borhan, MH Osman, MR Mat Yazid… - Mathematics, 2022 - mdpi.com
Light rail transit (LRT) systems are vital aspects of the worldwide endeavor to achieve
transport sustainability and have been essential in enhancing the economies of urban …

Evaluation of the impact of Covid-19 on air traffic volume in Turkish airspace using artificial neural networks and time series

N Gultekin, S Acik Kemaloglu - Scientific reports, 2023 - nature.com
In early 2020, the aviation sector was one of the business lines adversely affected by the
Covid 19 outbreak that affected the whole world. As a result, some countries imposed travel …

Air traffic demand forecasting with a bayesian structural time series approach

Y Rodríguez, OD Olariaga - Periodica Polytechnica Transportation …, 2024 - pp.bme.hu
Airport planning, and therefore the development of air infrastructure, depends to a large
extent on the demand forecast for the future. To plan investments in the infrastructure of an …

Hybrid feedforward ANN with NLS-based regression curve fitting for US air traffic forecasting

F Saâdaoui, H Saadaoui, H Rabbouch - Neural Computing and …, 2020 - Springer
Due to the rapid growth of the number of passengers over the few recent decades, air traffic
forecasting has become a crucial tool for digital transportation systems, playing a …

Machine learning for air transport planning and management

G Wild, G Baxter, P Srisaeng… - AIAA Aviation 2022 Forum, 2022 - arc.aiaa.org
View Video Presentation: https://doi. org/10.2514/6.2022-3706. vid In this work we compare
the performance of several machine learning algorithms applied to the problem of modelling …

Issues and solutions in air-traffic infrastructure and flow management for sustainable aviation growth: A literature review

H An, N King, SO Hwang - World Review of Intermodal …, 2019 - inderscienceonline.com
The demand for air transportation has continuously increased over the past few decades
and is expected to grow at 2% per annum over the next 20 years. However, airspace is …

Forecasting the international air passengers of Iran using an artificial neural network

F Nourzadeh, S Ebrahimnejad… - … of Industrial and …, 2020 - inderscienceonline.com
Forecasting passenger demand is generally viewed as the most crucial function of airline
management. In order to organise the air passengers entering Iran, in this study, the number …