A knowledge-and-data-driven modeling approach for simulating plant growth and the dynamics of CO2/O-2 concentrations in a closed system of plants and humans by integrating mechanistic and empirical models

摘要

Modeling and the prediction of material flows (plant production, CO2/O-2 concentrations, H2O) is an important but challenging task in the design and control of closed ecological life support systems (CELSS). The aim of this study was to develop a novel knowledge-and-data-driven modeling (KDDM) approach for simultaneously simulating plant production and CO2/O-2 concentrations in a closed system of plants and humans by integrating mechanistic and empirical models.