DocumentCode
1934701
Title
Prediction Model for Power Coal Blending Based on SVM
Author
Sun, Wei ; Zhang, Xing
Author_Institution
North China Electr. Power Univ., Baoding
Volume
5
fYear
2007
fDate
19-22 Aug. 2007
Firstpage
2982
Lastpage
2985
Abstract
According to the situation of blended coal´s property predicting, a new kind of prediction model for power coal blending based on support vector machine is established, then this paper makes experiments by using the real data, and the results compared with weighted averaging method and neural network show that SVM has higher prediction accuracy in the condition of few data, thus the model has great use value in the domain of power coal blending.
Keywords
blending; coal; mining industry; neural nets; support vector machines; neural network; power coal blending; prediction model; support vector machine; weighted averaging method; Accuracy; Conference management; Cybernetics; Energy management; Machine learning; Neural networks; Predictive models; Sun; Support vector machines; Virtual colonoscopy; BP neural network; Power coal blending; Prediction model; SVM;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location
Hong Kong
Print_ISBN
978-1-4244-0973-0
Electronic_ISBN
978-1-4244-0973-0
Type
conf
DOI
10.1109/ICMLC.2007.4370658
Filename
4370658
Link To Document