Systematic review of passenger demand forecasting in aviation industry

RA Zachariah, S Sharma, V Kumar - Multimedia tools and applications, 2023 - Springer
Forecasting aviation demand is a significant challenge in the airline industry. The design of
commercial aviation networks heavily relies on reliable travel demand predictions. It enables …

A literature review and citation analyses of air travel demand studies published between 2010 and 2020

S Wang, Y Gao - Journal of Air Transport Management, 2021 - Elsevier
Accurate forecasting of air travel demand is vital for the resource planning of the air
transportation industry. Therefore, identifying contributing factors and understanding the …

A novel passenger flow prediction model using deep learning methods

L Liu, RC Chen - Transportation Research Part C: Emerging …, 2017 - Elsevier
Currently, deep learning has been successfully applied in many fields and achieved
amazing results. Meanwhile, big data has revolutionized the transportation industry over the …

The hybrid PROPHET-SVR approach for forecasting product time series demand with seasonality

L Guo, W Fang, Q Zhao, X Wang - Computers & Industrial Engineering, 2021 - Elsevier
Demand forecasting is the basic aspect of supply chain management. It has important
impacts on planning, capacity and inventory control decisions. Seasonality is a common …

Forecasting the demand of the aviation industry using hybrid time series SARIMA-SVR approach

S Xu, HK Chan, T Zhang - Transportation Research Part E: Logistics and …, 2019 - Elsevier
In this study, a novel SARIMA-SVR model is proposed to forecast statistical indicators in the
aviation industry that can be used for later capacity management and planning purpose …

[PDF][PDF] Random forest and support vector machine on features selection for regression analysis

C Dewi, RC Chen - Int. J. Innov. Comput. Inf. Control, 2019 - ijicic.org
Feature selection becomes predominant and quite prominent in the case of datasets that are
contained with a higher number of variables. RF (Random Forest) has emerged as a robust …

Air transportation demand forecast through Bagging Holt Winters methods

TM Dantas, FLC Oliveira, HMV Repolho - Journal of Air Transport …, 2017 - Elsevier
This paper expands the fields of application of combined Bootstrap aggregating (Bagging)
and Holt Winters methods to the air transportation industry, a novelty in literature, in order to …

A multi-pattern deep fusion model for short-term bus passenger flow forecasting

Y Bai, Z Sun, B Zeng, J Deng, C Li - Applied Soft Computing, 2017 - Elsevier
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 …

Solar power output forecasting using evolutionary seasonal decomposition least-square support vector regression

KP Lin, PF Pai - Journal of Cleaner Production, 2016 - Elsevier
Renewable power output is an important factor in scheduling and for improving balanced
area control performance. This investigation develops an evolutionary seasonal …

Forecasting air passenger demand with a new hybrid ensemble approach

F Jin, Y Li, S Sun, H Li - Journal of Air Transport Management, 2020 - Elsevier
Analyzing and modeling passenger demand dynamic, which has important implications on
the management and the operation in the entire aviation industry, are deemed to be a tough …