高炉炉况评价系统的设计与实现

The Design and Realization of the Evaluation System for the Blast Furnace State

利用高炉指数化模型和评分方法来评价高炉炉况的好坏．提出了依据统计的观点，以提高炉况评价的符合率为目标的爬山搜索方法，其符合率为９６．３５％．构造了炉况评价系统中的参数自学习子系统，运行结果，其符合率为９５．７５％

The exponential model and evaluating method of the blast furnace are used to evaluate the quality of the blast furnace state. In order to improve the percentange of hits for evaluating the blast furnace state,it is very important to correctly decide the threshold value and weight of evaluation exponent. The hill climbing search algorithm which is for improving the confirmity of evaluating the blast furnace state is proposed in terms of statistical view and the parameter self learning subsystem in the evaluation system of the blast furnace state is constructed.