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Journal of Applied Sciences
  Year: 2009 | Volume: 9 | Issue: 6 | Page No.: 1001-1013
DOI: 10.3923/jas.2009.1001.1013
 
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Application of Artificial Neural Networks for Airline Number of Passenger Estimation in Time Series State

M. Zandieh, A. Azadeh, B. Hadadi and M. Saberi

Abstract:
This study presents an integrated Artificial Neural Networks (ANN) to estimate and predict airline number of passenger in Iran. All type of ANN-Multi Layer Perceptron (MLP) is examined to this estimation. The ANN models are implemented on MATLAB software. Auto-Correlation Function (ACF) is utilized to define input variables. Finally, the best type of ANN-MLP is determined with Data Envelopment Analysis (DEA). Kruskal-Wallis test is used for asses the impact of raw data, preprocessed data and post process method on ANN performance. Monthly airline number of passenger of Iran airline from 1993 to 2005 is considered as the case of this study.
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How to cite this article:

M. Zandieh, A. Azadeh, B. Hadadi and M. Saberi, 2009. Application of Artificial Neural Networks for Airline Number of Passenger Estimation in Time Series State. Journal of Applied Sciences, 9: 1001-1013.

DOI: 10.3923/jas.2009.1001.1013

URL: https://scialert.net/abstract/?doi=jas.2009.1001.1013

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