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Exploiting Neural Networks to Enhance Trend Forecasting for Hotels Reservations

  • Athanasius Zakhary
  • Neamat El Gayar
  • Sanaa El-Ola. H. Ahmed
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5998)

Abstract

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.

Keywords

Hide Node Forecast Method Forecast Horizon Trend Component Revenue Management 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Athanasius Zakhary
    • 1
  • Neamat El Gayar
    • 1
    • 2
  • Sanaa El-Ola. H. Ahmed
    • 1
  1. 1.Faculty of Computers and InformationCairo UniversityGizaEgypt
  2. 2.Center for Informatics Science, School of Communication and, Information TechnologyNile UniversityGizaEgypt

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