원문정보
보안공학연구지원센터(IJUNESST)
International Journal of u- and e- Service, Science and Technology
Vol.8 No.3
2015.03
pp.301-310
피인용수 : 0건 (자료제공 : 네이버학술정보)
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
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
저자정보
참고문헌
자료제공 : 네이버학술정보