Exploiting Neural Networks to Enhance Trend Forecasting for Hotels Reservations

Athanasius Zakhary*, Neamat El Gayar, Sanaa El Ola H. Ahmed

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)


Hotel revenue management is perceived as a managerial tool for room revenue maximization. A typical revenue management system contains two main components: Forecasting and Optimization. A forecasting component that gives accurate forecasts is a cornerstone in any revenue management system. It simply draws a good picture for the future demand. The output of the forecast component is then used for optimization and allocation in such a way that maximizes revenue. This shows how it is important to have a reliable and precise forecasting system. Neural Networks have been successful in forecasting in many fields. In this paper, we propose the use of NN to enhance the accuracy of a Simulation based Forecasting system, that was developed in an earlier work. In particular a neural network is used for modeling the trend component in the simulation based forecasting model. In the original model, Holt's technique was used to forecast the trend. In our experiments using real hotel data we demonstrate that the proposed neural network approach outperforms the Holt's technique. The proposed enhancement also resulted in better arrivals and occupancy forecasting when incorporated in the simulation based forecasting system.

Original languageEnglish
Title of host publicationArtificial Neural Networks in Pattern Recognition. ANNPR 2010
Number of pages11
ISBN (Electronic)9783642121593
ISBN (Print)9783642121586
Publication statusPublished - 2010
Event4th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition 2010 - Cairo, Egypt
Duration: 11 Apr 201013 Apr 2010

Publication series

NameLecture Notes in Computer Science
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference4th IAPR TC3 Workshop on Artificial Neural Networks in Pattern Recognition 2010
Abbreviated titleANNPR 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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