Intelligent ATC modeling by indoor navigation

In this paper, an intelligent algorithm for modeling and simulating the Air Traffic Control (ATC) is presented. Reducing the workload of ATC operators by using computers instead of humans, the algorithm decreases the human faults. In this regard, two methods, including Naïve Bayes classifier (NB) and neural network (NN), are employed to make the machines intelligent. Having used a huge number of data from radio signal strengths at determined positions, least-square and backpropagation algorithms are utilized to train and evaluation test of NB classifier and neural network, respectively. The experiments compare between these two methods; however, both of them show satisfactory results in the determination of the agents’ positions.

Keywords:

Air Traffic Control , Neural Network , Naïve Bayes classifier , Backpropagation , Artifitial Intelligent.