山东建筑大学学报2026，Vol.41Issue(2)：11-20,32,11.DOI:10.12077/sdjz.2026.02.002
基于深度学习与修正IMK模型的夹层叠合板受弯性能研究
Study on flexural performance of sandwich composite slabs based on deep learning and modified IMK model
摘要
Abstract
The flexural performance properties of ceramsite foamed concrete sandwich composite slabs is critical to the overall safety of building structures.However,predictive models for such slabs remain limited.To this end,five ceramsite foamed concrete sandwich composite slabs were designed for static loading tests in this paper.A refined finite element model was developed and validated.The test data and simulation data of the modified Ibarra-Medina-Krawinkler(IMK)model were integrated to construct a composite slab database,and a prediction model was established in combination with the BP neural network.The load-displacement curves generated by the prediction model and those from the tests were compared and analyzed.The results indicate that the evaluation indexes of the BP neural network prediction model combined with the modified IMK model have a maximum RMSE of 9.69,a maximum MAPE of 9.64%,and a minimum R2 of 0.94,indicating strong generalization capability and high prediction accuracy.The load-displacement curves generated by the prediction model are basically consistent with the test load-displacement curves,confirming that the proposed model can effectively simulate the flexural behavior of such composite slabs.关键词
叠合板/深度学习/受弯性能/BP神经网络/参数辨识Key words
composite slab/deep learning/bending behavior/BP neural network/parameter identification分类
建筑与水利引用本文复制引用
刘春阳,周光锴,栾开业..基于深度学习与修正IMK模型的夹层叠合板受弯性能研究[J].山东建筑大学学报,2026,41(2):11-20,32,11.基金项目
国家自然科学基金项目(52278507) （52278507）
山东省自然科学基金项目(ZR2022ME160) （ZR2022ME160）
北京工业大学重点实验室开放课题(2020B03) （2020B03）
