Neural emulator temperature mode of copper-nickel raw materials smelting in Vanyukov furnace
One of Vanyukov furnace smelting problems is large losses of non-ferrous metals with slag, which lead to lower process. Melt temperature significantly influences effective separation of melting products and consequently their chemical composition. The purpose of work is to create temperature smelting model of copper-nickel raw materials in Vanyukov furnace based on artificial neural networks and statistic data use. The elaborated model will create automatic control system supporting optimal temperature mode in furnace.