Prediction of the Slagging Characteristics of Coal Ash Based on Symmetric Fuzzy Cross Entropy and Vague Sets

Abstract:

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.

• Periodical: Applied Mechanics and Materials (Volume 302)
• Pages: 617-621
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.302.617
• Online since: February 2013
• Authors: Xiao Qiang Wen
• Keywords: Coal Ash, Predicting, Slagging, Symmetric Fuzzy Cross Entropy, Vague Set

References

[1] Chen L J, Wen X Q, Sun L F, et al, A summary of prediction methods for slagging properties of coal-fired boilers, Thermal Power Generation, vol. 16(2006), no. 6, p.1.

[2] W L Gau and D J Buehrer, Vague sets, IEEE Trans on Systems, Man and Cybernetics, vol. 23(1993), no. 2, p.610.

DOI: 10.1109/21.229476

[3] Zadeh L A, Fuzzy sets, Information and Control, vol. 8(1965), no. 3. p.338.

[4] Yang S C, A study on prediction of slagging in coal fired boilers at thermal power plant, Thermal Power Generation, vol. 13 (2003), no. 1, p.31.

[5] Ding S F, Digital pattern recognition and its applications based on information theory, Shandong: Shandong University of Science and Technology, (2004).