Reza, S.M. and Wah, T.Y. and Lahsasna, A. (2011) Applied data mining approach in ubiquitous world of air transportation. In: 4th International Conference on Computer Sciences and Convergence Information Technology, NOV 24-26, 2009 , Seoul, SOUTH KOREA.
Full text not available from this repository.Abstract
Noise is a big problem for people living near airports, therefore the public, airport authorities and pilots are looking for ways to reduce the noise in the vicinity of populated areas. Optimal solution would be flight paths that are farthest from those areas, and worst paths are those, that just go above them. There are two classes of paths, namely optimal and non-optimal ones. This paper is going to use one of successfully used data mining techniques, namely neural network, which is capable of recognizing patterns. We used some coordinates of various flight paths as input for learning purposes of Neural Network, and defined two classes representing the optimal and non-optimal flight paths. The results have shown that this technique is well capable of recognizing the optimal and non-optimal flight paths. This technique can be used to reduce the noise.
Item Type: | Conference or Workshop Item (Paper) |
---|---|
Funders: | UNSPECIFIED |
Additional Information: | Univ Malaya, Fac Comp Sci & Informat Technol, Kuala Lumpur, Malaysia |
Uncontrolled Keywords: | Data Mining; Neural Networks; Noise Reduction |
Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science |
Divisions: | Faculty of Computer Science & Information Technology |
Depositing User: | Mr. Faizal Hamzah |
Date Deposited: | 13 Oct 2011 03:02 |
Last Modified: | 13 Oct 2011 03:02 |
URI: | http://eprints.um.edu.my/id/eprint/2188 |
Actions (login required)
View Item |