CO Pollutant Evaluation Using Two Artificial NeuralNetwork Algorithms in Tehran

Air pollution is one of the most important environmental problems of the last century that threatens human health. Air pollution is the presence of one or more pollutants in the open air that are harmful to humans, animals, plants and property. Air pollution unacceptably disturbs the comfortable use of life. In this paper, the CO pollutant city was evaluated in Tehran using two artificial neural network algorithms BFGS Quasi-Newton and Resilient Backpropagation. The result indicated that the Resilient Backpropagation algorithm has less error with five hidden layers, and its root mean square is equal to ۱.۱۱۳۰.

Keywords:

Air pollution , Artificial Neural Network , CO , RS