Context Dependent Controller by Overlapped Neural Networks for Performance Metrics Revision

We introduce a novel approach for problems regardless of sufficiency or accuracy of their historical observations or lab simulation data. Our approach is based on imposing a context of problem performance metrics into networks and gaining the enhancement towards its satisfactory state. We use an overlapped system of back propagation neural networks for our purpose. A main neural network is responsible for mapping input and output relation while a regulatory neural network evaluates the performance metrics satisfaction. We provide special training and testing algorithms for the overlapped system that guarantees a synchronized solution for both neural networks. An example of traffic control problem is simulated. The result of simulation shows a great enhancement of the solution using our approach