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.
[1]
Mohamed Medhat Gaber,et al.
Ubiquitous data stream mining
,
2004
.
[2]
D. Signorini,et al.
Neural networks
,
1995,
The Lancet.
[3]
Robert J. Bernhard,et al.
Low frequency noise study.
,
2007
.
[4]
M. Betke,et al.
The Camera Mouse: visual tracking of body features to provide computer access for people with severe disabilities
,
2002,
IEEE Transactions on Neural Systems and Rehabilitation Engineering.
[5]
Dimitrios Gunopulos,et al.
Indexing Multidimensional Time-Series
,
2004,
The VLDB Journal.