Modeling of CO distribution in Istanbul using Artificial Neural Networks

Abstract

Artificial Neural Network (ANN) is one of the popular methods in optimization of complex engineering problems compared to the classical statistical methods. ANN approximates non-linear input-output variables and finds an optimum correlation between these variables. Thus the structure of the overall system is simplified. ANN function approximation is achieved by identifying the input-output pattern pairs, using the following steps: (I) Selection of the neural structure (namely the number of layers and that of neurons), (II) Training of ANN using Back-Propagation (BP) algorithms. ANN coefficients can be trained as any system performance characteristics by monitoring test data. (III) Validation of the network to verify generalization capability.