A BCMO-DNN algorithm for vibration optimization of functionally graded porous microplates

The authors propose a novel BCMO-DNN algorithm for vibration optimization of functionally graded porous microplates. The theory is based on a unified framework of higher-order shear deformation theory and modified strain gradient theory. A hybrid combination of deep learning neural network and balancing composite motion optimization is developed to solve the optimization problems and predict stochastic vibration behaviors of functionally graded porous microplates with uncertainties of material properties.