Solving an optimal control problem of complex heat transfer using machine learning methods

Abstract

The problems of the non-stationary complex heat transfer have been considered in the work. An optimization algorithm based on machine learning methods has been proposed. The algorithm uses a neural network trained on a dataset of numerical experiments to predict the value of a chosen quality functional. Dual annealing method has been used to minimize neural network prediction function while varying boundary parameters. The obtained results are verified by comparison with numerical experiments.