Machine Learning Techniques for Solving Constrained Engineering Problems

This paper focuses on the application of the supervised machine learning technique. The main objective is to construct models of objective functions. Sixteen different varieties of benchmark test functions and three well-known engineering design problems are evaluated by machine learning technique. The Artificial Neural Networks (ANNs) technique is used for constructing models. For the sake of accuracy check, three metrics are used; Mean Square Error (MSE), Root Mean Square Error (RMSE) and Maximum Absolute Error (MAE).