Impact of temperature on mechanical properties and dimensional stability in a novel gradient pressure bamboo flattening technique

Wang, Xianke; Su, Na; Chen, Xiaohan; Fei, Benhua; Ma, Xinxin; Liu, Huanrong; Miao, Hu; Fang, Changhua

doi:10.1016/j.conbuildmat.2024.136258

Construction and Building Materials

2024

DOI: 10.1016/j.conbuildmat.2024.136258

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Impact of temperature on mechanical properties and dimensional stability in a novel gradient pressure bamboo flattening technique

Xianke Wang,

Na Su,

Xiaohan Chen

et al.

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Bi-Directional Prediction Model for Hot Pressing Production Parameters and Quality of High-Performance Bamboo-Based Fiber Composites Based on cHGWOSCA-SVR

Ding,

Zhang,

Meng

et al. 2024

Applied Sciences

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In the hot press process of high-performance bamboo-based fiber composites, there is a highly nonlinear relationship between the production parameters of hot press and the quality parameters of the finished boards. Consequently, it is challenging to accurately predict the quality of the boards based on the given production parameters, and it is equally difficult to preset the production parameters to achieve the desired board quality. The current approach relies on manual experience, which may result in subpar board quality and material waste. To address these issues, this paper proposes a bi-directional prediction model based on cHGWO-SCA-SVR, using the collaboration-based hybrid GWO-SCA optimizer to optimize the relevant parameters of the SVR, and then accurately predicting the production parameters and the quality of the finished boards in both directions. Finally the cHGWO-SCA-SVR prediction model achieves an average R2 of 0.9591 for the forward prediction model and lower MAE and MSE values compared to other models; for the reverse prediction model, it attains an average R2 of 0.9553 and lower MAE and MSE values compared to other models. The results demonstrate the superiority of the cHGWO-SCA-SVR prediction model in comparison with other existing models, proving its significance in guiding the production of high-performance bamboo-based fiber composites by hot compression.

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Bi-Directional Prediction Model for Hot Pressing Production Parameters and Quality of High-Performance Bamboo-Based Fiber Composites Based on cHGWOSCA-SVR

Ding,

Zhang,

Meng

et al. 2024

Applied Sciences

View full text Add to dashboard Cite

show abstract

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Impact of temperature on mechanical properties and dimensional stability in a novel gradient pressure bamboo flattening technique

Cited by 1 publication

References 33 publications

Bi-Directional Prediction Model for Hot Pressing Production Parameters and Quality of High-Performance Bamboo-Based Fiber Composites Based on cHGWOSCA-SVR

Bi-Directional Prediction Model for Hot Pressing Production Parameters and Quality of High-Performance Bamboo-Based Fiber Composites Based on cHGWOSCA-SVR

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