- 期刊
- OpenAccess
Development of a Neuro-Fuzzy Model for Airline Passenger Forecasting
並列摘要
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.
延伸閱讀
- Jiang, S. C. (2007). Tourist Arrival Forecasting Using Adaptive Fuzzy Network. 文大商管學報, 12(1), 187-206. https://doi.org/10.30163/BR.200706.0008
- 林成翰（2006）。Using Fuzzy Integral Logit Model on the Choice Behavior of Domestic Airlines〔碩士論文，國立臺中科技大學〕。華藝線上圖書館。https://www.airitilibrary.com/Article/Detail?DocID=U0061-1811200915323665
- 郭仲偉（2008）。A Study on Forecasting Potential Primary Hub Cities for Air Passenger Transport〔博士論文，國立臺灣大學〕。華藝線上圖書館。https://doi.org/10.6342/NTU.2008.01377
- 張育維（2011）。A Novelty Hybrid Forecast Model to Forecast Tourism Demand。管理實務與理論研究，5(3)，74-86。https://doi.org/10.29916/JMPP.201109.0005
- Yang, H. T. (2016). Aviation Safety Forecasting by Artificial Neural Networks [master's thesis, Chung Yuan Christian University]. Airiti Library. https://doi.org/10.6840/cycu201600625