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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

A demand trend change early warning forecast model for the city of Sao Paulo multi-airport system

Full text
Author(s):
Scarpel, Rodrigo Arnaldo [1]
Total Authors: 1
Affiliation:
[1] ITA, Sao Jose Dos Campos - Brazil
Total Affiliations: 1
Document type: Journal article
Source: TRANSPORTATION RESEARCH PART A-POLICY AND PRACTICE; v. 65, p. 23-32, JUL 2014.
Web of Science Citations: 4
Abstract

The need of accurate forecasts of air passenger numbers to assist managerial decision making for both short and long terms is well recognized and a central problem on both short and long term forecasting is how to handle future trend. The aim of this paper is to develop a demand trend change early warning forecast model (EWFM) for the city of Sao Paulo multi-airport system (SPMARs). For SPMARs the EWFM is based on the combination of leading indicators and alarms against possible occurrence of changes on trend component of the monthly number of domestic air passengers. A topdown induction procedure is employed to identify leading indicators to provide an interpretable prediction procedure to support the development of scenarios for future demand trend. Results show that changes on such demand trend are mostly associated to changes on the economic activity and six different scenarios were built combining the identified leading indicators. The EWFM was employed to assist managerial decision making for both short and long terms in order to evaluate different alternatives to prevent congestion delay occurrences and to support infrastructure planning. (C) 2014 Elsevier Ltd. All rights reserved. (AU)

FAPESP's process: 13/22416-4 - Data mining on early detection of congestion delays for Brazilian airports
Grantee:Rodrigo Arnaldo Scarpel
Support Opportunities: Regular Research Grants