Abstract

This article explores the vibration response of the hybrid composite structure with the aid of the adaptively tuned deep neural network (DNN). In order to find the features of the design-points, the semi-numerical technique is applied to the governing differential equations of the system acquired on the foundation of the kinematic theory with refined higher order terms. Considering higher order terms made the accuracy of this analysis suitable for moderately thick plates as well as thin ones. DNN is trained for vibrational characteristics of the design-points by employing adaptive learning rate method as the high-speed optimizer. Accuracy of the semi-numerical method (used for determining the design-points) is evaluated through the comparison with the results reported in the published studies. While, the validity of the DNN-based model in predicting the response of the system at design-points is tested and confirmed by analyzing the trend of mean squared error.

摘要

本文借助自适应调谐深度神经网络 (DNN) 探索混合复合材料结构的振动响应。为了找到设计点的特征，将半数值技术应用于在运动学理论的基础上获得的具有细化高阶项的系统的控制微分方程。考虑到高阶项使得该分析的准确性适用于中厚板和薄板。DNN 通过采用自适应学习率方法作为高速优化器来针对设计点的振动特性进行训练。半数值方法（用于确定设计点）的准确性通过与已发表研究报告的结果进行比较来评估。尽管，