Applying the Random Forest Method to Improve Burner Efficiency

Fuel power plants are one of the main sources pollutant emissions, so special attention should be paid to improving efficiency fuel combustion process. The mathematical modeling processes in chamber makes it possible reliably predict and find best dynamic characteristics operation a plant, order quantify emission harmful substances, as well environmental technical economic various regime control actions measures, use new types composite fuels. purpose this article is illustrate how machine learning methods can play an important role predicting performance paper proposes model unsteady turbulent process, presents with combined burner, performs numerical study using STAR-CCM+ multidisciplinary platform. influence input indicators on burner devices, which evaluated by several parameters at output, investigated. In case, three states burners assumed: optimal, satisfactory unsatisfactory.