A light gradient boosting machine-based method for predicting the dynamic response of functionally graded plates

dc.contributor.authorDo, Thi Thanh Dieu
dc.contributor.authorNguyen, Hoang Yen
dc.date.accessioned2024-08-22T03:58:42Z
dc.date.available2024-08-22T03:58:42Z
dc.date.issued2024
dc.description10 p.
dc.description.abstractThe primary objective of this paper is to efficiently predict the dynamic response of functionally graded plates using LightGBM – a light gradient boosting machine, without reliance on supplementary analysis tools. To obtain the optimal LightGBM model, a dataset comprising 1,000 pairs of input and output is generated through iterations using a combination of isogeometric analysis (IGA) and third-order shear deformation plate theory (TSDT). In this model, the input is represented by a power index which governs the material distribution of the plate, and the output comprises 200 values illustrating deflection over time. To demonstrate the effectiveness of LightGBM in terms of accuracy and computational time, the results obtained by the proposed model are compared to those achieved with the optimal ANN, XGBoost models, and IGA.
dc.identifier.citationNguyen Tat Thanh University. (2024). Journal of Science and Technology - NTTU, Volume 7, Issue 2. ISSN 2615-9015.
dc.identifier.issn2615-9015
dc.identifier.urihttps://oerrepository.ntt.edu.vn/handle/298300331/70
dc.language.isoen
dc.publisherNguyen Tat Thanh University
dc.relation.ispartofseriesJournal of Science and Technology - NTTU; Vol.7, No. 2
dc.titleA light gradient boosting machine-based method for predicting the dynamic response of functionally graded plates
dc.typeArticle
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