Research on unburned combustible forecast in fly ash of the coal-fired boiler based on Genetic Algorithm and Artificial Neural Network
The boiler fuel burning is the main basis to evaluate the energy saving. This paper combined the genetic algorithm and artificial neural network to model the burning process of the boiler fuel, in order to forecast the unburned combustible in flue dust of the coal-fired boiler. Use the powerful optimizing of GA to narrow the search range, then use ANN to optimize accurately. It can prevent the BP from sinking into local minimum, low convergence rate oscillation effect and other disadvantages. And then, more accurate output data of the black box can be obtained.