Prediction of the Slagging Characteristics of Coal Ash Based on Symmetric Fuzzy Cross Entropy and Vague Sets
A prediction model was built to predict the slagging characteristics of coal ash based on the theory of symmetric fuzzy cross entropy and vague sets. Softening temperature, SiO2-Al2O3 ratio, Alkali-acid ratio, silicon percentage of value were selected as input vectors. Firstly, the vague values of the selected samples were calculated based on vague sets theory, and then the similarity degree was evaluated based on symmetric fuzzy cross entropy. The prediction results prove that the predicting accuracy rate of the new pattern recognition model is 90%. So, the model built here is reasonable and feasible and meets the requirement of engineering.
X. Q. Wen, "Prediction of the Slagging Characteristics of Coal Ash Based on Symmetric Fuzzy Cross Entropy and Vague Sets", Applied Mechanics and Materials, Vol. 302, pp. 617-621, 2013