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A Genetic Algorithm-Based Grey Model Combined with Fourier Series for Forecasting Tourism Arrivals in Langkawi Island Malaysia

  • Abdulsamad E. Yahya
  • Ruhaidah SamsudinEmail author
  • Ani Shabri IlmanEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1073)

Abstract

Accurate prediction of tourism demand is an important issue for the tourism industry because it can efficiently provide basic information for better tourism planning, along with the desire to reduce risk and uncertainty. To successfully achieve an accurate prediction of tourism demand, this study develops a new forecasting model by combining the Fourier residual modification with an optimized Grey model GM (1, 1). Genetic algorithms (GA) were optimally used simultaneously to select the parameter of the GM (1, 1). For illustration of the proposed model, the monthly international tourist arrivals to Langkawi Island Malaysia has been used as a sample study. Empirical results indicate that the proposed forecasting model demonstrates a superior performance to other methods in terms of forecasting accuracy.

Keywords

ARIMA Grey Genetic algorithms Artificial neural network Fourier series 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Northern Border University, Kingdom of Saudi ArabiaArarSaudi Arabia
  2. 2.School of Computing, Faculty of EngineeringUniversiti Teknologi MalaysiaSkudaiMalaysia
  3. 3.Department of Mathematics, Faculty of ScienceUniversiti Teknologi MalaysiaSkudaiMalaysia

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