论文信息 - A multivariate neural forecasting modeling for air transport – Preprocessed by decomposition: A Brazilian application

A multivariate neural forecasting modeling for air transport – Preprocessed by decomposition: A Brazilian application

An artificial neural forecasting model is developed for air transport passenger analysis. It uses a preprocessing method that decomposes information to reveal relevant features from the data. It is found that neural processing outperforms the traditional econometric approach and offers generalization on time series behavior, even where there are only small samples.

J. M. Seixas | K.P.G. Alekseev | J. Seixas | K. Alekseev

[1] Gianluigi Rech,et al. Forecasting with artificial neural network models , 2002 .

[2] Simon Haykin,et al. Neural Networks: A Comprehensive Foundation , 1998 .

[3] Michael Y. Hu,et al. A simulation study of artificial neural networks for nonlinear time-series forecasting , 2001, Comput. Oper. Res..

[4] Sharon Hormby,et al. A Large-Scale Neural Network for Airline Forecasting in Revenue Management , 1998 .

[5] V. Thamizh Arasan,et al. Modeling for Air Travel Demand , 1992 .

[6] J.M. de Seixas,et al. Neural discriminating analysis on preprocessed data , 1999, ICECS'99. Proceedings of ICECS '99. 6th IEEE International Conference on Electronics, Circuits and Systems (Cat. No.99EX357).

[7] William Remus,et al. Time series forecasting using neural networks: should the data be deseasonalized first? , 1999 .

[8] William Remus,et al. Neural Network Models for Time Series Forecasts , 1996 .

[9] Thomas Kolarik,et al. Time series forecasting using neural networks , 1994, APL '94.

[10] Alan V. Oppenheim,et al. Discrete-Time Signal Pro-cessing , 1989 .