Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications

Short-term Forecasting Method of Air Traffic Flow based Neural Network Ensemble

Authors
Ming Zhang, Kai Liu, Hui Yu, Jue Yu
Corresponding Author
Ming Zhang
Available Online May 2016.
DOI
10.2991/wartia-16.2016.231How to use a DOI?
Keywords
air transportation, short-term prediction,disuniform data, neural network ensemble, k-means clustering, 3 Principle,fuzzy membership
Abstract

In this research, in order to address interferences of air traffic from complex factors like weather and local data abnormality of radar samples, fuzzy clustering and neural network ensemble were introduced into the short-term forecasting of air traffic flow. Firstly, with K-means cluster analysis, this research compared traffic volume at different time with that of each clustering center to identify the temporal clustering of traffic volume. Secondly, according to different data sets from clustering analysis, corresponding neural network models were established. On the basis of Bagging method, a neural network ensemble weight allocation algorithm of fuzzy subordinative degree was also built to identify weight of each neural network and to establish neural network ensembles model. Finally, according to 3 principle of normal distribution, abnormal data out of Section ( 3 , 3 ) was cleaned and short-term forecasting results were acquired. Our model showed superior results of short-term radar data forecasting for Shanghai Terminal Area, overmatching regression analysis and neural network forecasting. The experiment verified that the method is valid and feasible for short-term forecasting of air traffic flow.

Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
Series
Advances in Engineering Research
Publication Date
May 2016
ISBN
978-94-6252-195-7
ISSN
2352-5401
DOI
10.2991/wartia-16.2016.231How to use a DOI?
Copyright
© 2016, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Ming Zhang
AU  - Kai Liu
AU  - Hui Yu
AU  - Jue Yu
PY  - 2016/05
DA  - 2016/05
TI  - Short-term Forecasting Method of Air Traffic Flow based Neural Network Ensemble
BT  - Proceedings of the 2016 2nd Workshop on Advanced Research and Technology in Industry Applications
PB  - Atlantis Press
SP  - 1087
EP  - 1094
SN  - 2352-5401
UR  - https://doi.org/10.2991/wartia-16.2016.231
DO  - 10.2991/wartia-16.2016.231
ID  - Zhang2016/05
ER  -