Abstract:

By selecting dry ash-free volatile matter（Vdaf）, maximum plastic zone thickness （Y） and height and width ratio of coking chamber （L/B）as independent variables, the production data of 4 different type coke ovens are analyzed through the clone selection algorithm based on gene expression, and the predictive model for coke quality is established. In comparison with the predictive models obtained with the method and regression analysis method, the error of the coke quality predictive model obtained by the method is far less than that obtained by regression analysis method, the model can meet the actual production requirement better and provides the theoretical base for getting coal blending ratio quickly and accurately for coking plant.