Using Autoregressive Polynomial Regression Models to Study Moisture Content Dynamics in Wood

This study explores the complex relationship between wood moisture content and environmental factors, temperature and relative humidity. Utilizing a novel Autoregressive Polynomial Regression Model (APRM), data from sensors placed in reconstituted bamboo and pine planks at various positions were analyzed. The APRM, adept at handling polynomial and interaction terms, revealed a nuanced, non-linear relationship between moisture content and environmental conditions. The research findings underscore significant material-specific differences in response to environmental changes. This study not only contributes to the understanding of wood-environment interactions but also demonstrates the efficacy of APRM in environmental science, providing a foundational approach for future research in this field.