Hopfield Neural Networks for Aircrafts' Enroute Sectoring: KRISHAN-HOPES
Krishan Kumar · 2016
Air traffic controlling is a very complex task for the air port personnel. Hence the emphasis on some new advance computing techniques had always been a great and important area of research. Hopfield neural networks or simply Hopfield nets, a widely used popular category of feedback neural network or recurrent neural networks may play a very important role in handling issues related to air traffic control. As Hopfield nets provide a model for the memory of human brain and therefore they can memorize the input patterns of any real life problem. Hence these nets can be efficiently and effectively used for the air space sectoring problem. In this paper, a way to divide the existing space scenario in different sectors using Hopfield nets is presented. It is found that this method is appropriate for making the sectors of a congested busy air space. The result shows that algorithm gives the near optimal solution for 48 nodes or aircrafts.