Neural network modeling of vector multivariable functions in ill-posed approximation problems
I. A. Kruglov, O. A. Mishulina · Journal of Computer and Systems Sciences International · 2013
A neural network solution of the ill-posed inverse approximation problem of a multivariable vector function based on of a committee of multilayer perceptrons is proposed. A nonlinear adaptive decision-making rule by the committee is developed that improves the accuracy compared with other neural network solutions of the inverse problem. Using a model example, the accuracy characteristics of the method are shown. An applied engineering problem is considered and the results of its solution by the proposed method are presented.