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This project presents an application of artificial neural network (ANN) approach to the simulation and prediction of acid deposition conditions in the United States. The previous research is mainly focused on the effect of emission. However, with the increase of NO x emissions, acid deposition problem could become more serious in some areas despite stricter(More)
This Paper presents an efficient approach for the fast computation of inverse continuous time variant functions with the proper use of Radial Basis Function Networks (RBFNs). The approach is based on implementing RBFNs for computing inverse continuous time variant functions via an overall damped least squares solution that includes a novel null space vector(More)
In this article, a novel technique for non-linear global optimization is presented. The main goal is to find the optimal global solution of non-linear problems avoiding sub-optimal local solutions or inflection points. The proposed technique is based on a two steps concept: properly keep decreasing the value of the objective function, and calculating the(More)