doi: 10.18178/ijfcc.2017.6.2.491
Study on the Prediction Method of Fusion Recognition for Characteristic Information of Coal Spontaneous Combustion
Wei-Feng Wang
1
,
Jun Deng
1,*
,
Yuan-Bin Hou
2
,
Nai-Guo Wang
1,3
- 1 School of Safety Science and Engineering, Xi’an University of Science and Technology, Xi’an, Shaanxi 710054, China.
- 2 School of Electrical and Control Engineering, Xi’an University of Science and Technology, Xi’an, Shaanxi 710054, China.
- 3 Shandong Xinjulong Energy Limited Liability Company, Heze, Shandong 274918, China.
Abstract
To solve the technical problems of identificationfor the dangerous degree of coal spontaneous combustion, thecoal spontaneous combustion process is divided into threestages: slow oxidation, accelerating oxidation and intenseoxidation in the paper. The prediction method of fusionidentification for characteristic information of coal spontaneouscombustion is proposed and the sensitivity index of coalspontaneous combustion degree is determined. The quantitativerelationship of the characteristic temperature of coalspontaneous combustion and the gas concentration of eachindex is determined by polynomial least squares fitting methodaccording to the sample test data. The different feature statesare classified by SVM and PSO-SVM algorithm. The criterionof the diagnosis and early warning of coal spontaneouscombustion is given according to the results of the data level andfeature level. The proposed method can effectively solve theproblem of low recognition rate. The experiment shows that theprediction classification accuracy of SVM is 80%, theprediction classification accuracy of PSO - SVM isapproximately 100%. The PSO-SVM algorithm cansignificantly improve the prediction accuracy compared withthe traditional method, which provides criterion for thediagnosis and early warning of coal spontaneous combustion.The classification identification of the dangerous degree of coalspontaneous combustion is implemented. It is of greatsignificance and practical application value for improving thelevel of prevention and control technology of coal spontaneouscombustion early hazards.
Keywords
- Coal spontaneous combustion
- characteristicinformation
- fusion recognition
- prediction method
How to Cite
Wei-Feng Wang, Jun Deng, Yuan-Bin Hou, and Nai-Guo Wang, "Study on the Prediction Method of Fusion Recognition for Characteristic Information of Coal Spontaneous Combustion," International Journal of Future Computer and Communication, vol. 6, no. 2, pp. 67-71, 2017. https://doi.org/ 10.18178/ijfcc.2017.6.2.491
Copyright & License
Copyright © 2017 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).