Student
DryMAMBA: simulation and predction in drying process in the potato by State Space model
Please login to view abstract download link
Drying in porous media is a critical process in industries such as food production and paper manufacturing, where multiple physical effects must be considered: fluid flow, phase change heat transfer, and the transport of the involved liquids and gases. DryMamba leverages data from 100 simulations of potato drying to learn the coupled physical laws of temperature fields, humidity fields, and permeability through deep learning techniques. Our model demonstrates robust performance on a test dataset, effectively simulating the potato drying process with high accuracy and predictive reliability.
