Title :
Prediction Model for Power Coal Blending Based on SVM
Author :
Sun, Wei ; Zhang, Xing
Author_Institution :
North China Electr. Power Univ., Baoding
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;
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
DOI :
10.1109/ICMLC.2007.4370658
