Earticle

초록

영어

The combination forecasting model IOWGA-EMD-ARMA-WNN is proposed in this paper. The randomness, periodicity and tendency of the original data are showed by EMD decomposition in EMD-ARMA model. WNN combines the advantages of wavelet analysis and BP neural network and improves the learning efficiency and forecasting accuracy. The weight of combination model is decided by forecasting precision of EMD-ARMA model and WNN model based on IOWGA method. At last, the IOWGA-EMD-ARMA-WNN model is used to forecast monthly inboard tourism demand of China and the results show that the proposed combination model has better performance on forecasting accuracy compared with the other models.

목차

Abstract
 1. Introduction
 2. The Nonlinear Combination Forecasting Method
  2.1 The EMD-ARMA Forecasting Model
  2.2 The Wavelet Neural Network Model
  2.3 IOWGA Operator
  2.4 The IOWGA-EMD-ARMA-WNN models
 3. Experiment and Simulation Analysis 
 4. Conclusion
 References

키워드

저자

• Yaping Wang [ Department of Xi'an International University Xi'an City Shanxi Province 710077, PR China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605