Methods of Artificial Intelligence for Simulation of Gasification of Biomass and Communal Waste

Artificial intelligence (AI) methods can simulate accurately outcomes of gasification processes based on real data sets. Quality and composition of gas obtained from solid fuels depend on the temperature of the gasifying agent (air or steam) and the composition of used solid waste (biomass, industrial waste or combustibles from municipal solid waste, such as plastics, textile, wood, paper, tires, etc.). To simulate the gasification processes, a symbolic regression software AI Feynman is tested. Finally, the results of symbolic regression are compared with measured data. The results indicate that symbolic regression of AI Feynman is useful for modelling of biomass gasification technologies from measured data.