Intelligent Air Traffic Control using Neural Networks
The air traffic control systems used by airports, worldwide, are still depending on systems and algorithms which were developed almost forty years ago. Now the complexity of air traffic control has increased in complexity due to increase in aircrafts and airports. The complex decisions such as take off, landing etc. are carried out by human traffic controllers. The controllers depending on various parameters such as availability of runway, climate conditions etc. make the decision and such decisions are highly prone to errors. Safety is a major factor limiting the automation of existing air traffic control systems. This project deals with automation of existing air traffic control system using neural networks as a basis. Neural networks come's under artificial intelligence and has been found to be effective in many fields for making decisions such as in robotics, Medical field etc. Neural networks learn by exposure. The algorithm used is back propagation network for decision making. The network is trained using some predetermined inputs and later the network will be capable of making decisions of its own with minimal or zero error. MATLAB can be used for training the neural network.