Controlling combustion process in power boiler by genetic algorithm and neural network

An analyse of evolutionary algorithm operation allows us to understand how controlled spontaneity of an individual specimen leads to dynamic order of the whole community that efficiently uses emerging adaptive possibilities. This paper presents sequel of research concerning implementation of GA in controlling burning process in industrial conditions. A simulation was conducted and proved that implementing GA to the process is possible and brings improvement of flue gases parameters, what is a direct measure of power boiler quality of work, both in ecologic and economical way.