Rescaling of variables in back propagation learning
Neural Networks
An introduction to neural computing
An introduction to neural computing
IEEE Spectrum
Fundamentals of neural networks: architectures, algorithms, and applications
Fundamentals of neural networks: architectures, algorithms, and applications
Air traffic control and alert agent
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Agent-Based Control for Networked Traffic Management Systems
IEEE Intelligent Systems
Modeling time and space metering of flights in the national airspace system
WSC '04 Proceedings of the 36th conference on Winter simulation
Traffic flow management modeling and operational complexity
WSC '04 Proceedings of the 36th conference on Winter simulation
Applying statistical control techniques to air traffic simulations
WSC '04 Proceedings of the 36th conference on Winter simulation
Multirobot systems: a classification focused on coordination
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Toward a systems- and control-oriented agent framework
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
| Hi-index | 0.00 |
Due to a dramatic increase in air traffic around the globe, the tasks for air traffic controllers have increased multifold. This work aims to develop an air traffic control to prioritize landing sequences assigned to planes when, unexpectedly, a large number of planes approach the airfield. Two alternatives are proposed: one is based on rule-based expert system and another on artificial neural networks. The author shows that each of the models helps to optimize the prioritization of overall landing requests, with exception only to a situation of a larger number of emergencies. Further, a combination of these approaches is discussed to show that it does help in minimizing time to handle landing sequences during emergencies.