The invention discloses a method for performing
nonlinear prediction on
coke quality on the basis of cohesiveness and
coal-rock indexes of single
coal, which provides important technical guarantee for improving the stability and quality of
coke produced by
coke making enterprises. The method comprises the following steps of: establishing an information
database storing qualities and coke quality indexes of the single
coal for coking, and inputting the cohesiveness indexes and the coal-rock indexes of the single coal for coking into the coal information
database; establishing a coal quality prediction model, and predicting quality indexes of matched coal by virtue of a clustering and
support vector machine; defining the quality indexes of the matched coal, and predicting quality indexes of the coke according to the quality indexes of the single coal; and establishing a model for predicting the crushing strength and
abrasive resistance of the coke. The invention further provides a coke quality
prediction system with optimized
coal blending of coal-rock, which aims to stabilize and improve the coke quality and reduce the
coal blending cost, can form a prediction model with multiple parameters and high accuracy for the coal quality indexes and the coke quality indexes, and simultaneously, has a real-time updating function or a manual intervention function.