Title
Artificial neural networks to estimate the forecast of tourism demand in Peru
Date Issued
01 November 2019
Access level
metadata only access
Resource Type
conference paper
Author(s)
Ramos-Carrasco R.
Galvez-Diaz S.
Alvarez-Merino J.
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
Abstract
Service companies, for the most part, do not have physical inventories that allow them to cushion demand variability. The high logistics costs of each process of the company are the reflection of these differences in the forecast. For this reason, having a successful demand forecast will generate a competitive advantage in companies that take these processes with interest. In the present work it is possible to estimate the amount of tourist packages that will be sold in the next three months using ANN (artificial neural networks) that present a decrease in the error of the current situation of 9.89% which, together with a forecast management system of adequate demand, it was thus possible to reduce the logistics costs of the services company by up to 33%.
Language
English
OCDE Knowledge area
Ingeniería industrial Robótica, Control automático
Scopus EID
2-s2.0-85082388067
Resource of which it is part
SHIRCON 2019 - 2019 IEEE Sciences and Humanities International Research Conference
ISBN of the container
9781728138183
Conference
2019 IEEE Sciences and Humanities International Research Conference, SHIRCON 2019 Lima 13 November 2019 through 15 November 2019
Sources of information: Directorio de Producción Científica Scopus