Development of a neuro-fuzzy model for airline passenger forecasting

Chuen Jyh Chen, Shih Ming Yang, Zi Cheng Wang

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)

Abstract

A five-layer neuro-fuzzy model with Sugeno fuzzy rules is developed to model the dynamics of airline passengers. The effectiveness in modeling, prediction and forecasting is validated by a set of data containing the consumer price index, the exchange rate, the gross national product, and the number of airline passengers traveling abroad from 1995 to 2007. A modified moving average method is applied to predict the input set for the model in forecasting the number of airline passengers. Simulation results show that the neuro-fuzzy model with Sugeno fuzzy rules is effective in prediction and accurate in forecasting. The input error from the modified moving average method is attenuated by the neuro-fuzzy model to yield better forecasting results.

Original languageEnglish
Pages (from-to)169-176
Number of pages8
JournalJournal of Aeronautics, Astronautics and Aviation
Volume44
Issue number3
Publication statusPublished - 2012 Sep

All Science Journal Classification (ASJC) codes

  • Aerospace Engineering
  • Space and Planetary Science

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