Abstract
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
Original language | American English |
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Title of host publication | Proceedings of the 5th International Conference on Cognitive Information (ICCI’06) |
DOIs | |
State | Published - 2006 |
DC Disciplines
- Engineering
- Computer Engineering