Mechanics-based deep learning framework for predicting deflection of functionally graded composite plates using an enhanced whale optimization algorithm

This paper introduces a novel deep learning framework for predicting the normalized and non-dimensional deflection of functionally graded composite plates subjected to sinusoidal loading. The proposed approach integrates a deep neural network (DNN) with a novel enhanced whale optimization algorithm (EWOA) to optimize deflection predictions considering mechanical parameters as input data, including stress, strain, plate geometry, and boundary conditions. The deflection outputs are expressed in both normalized and non-dimensional forms, demonstrating a robust and generalizable prediction model applicable to various structural configurations. During the training phase, the proposed EWOA significantly enhances…