Title :
Method Study of Forecasting Gas Outburst Based on Rough Set
Author :
Zhang, Haining ; Zhu, Zhenyu ; Wang, Xibin
Author_Institution :
Comput. & Inf. Eng. Dept., Heilongjiang Inst. of Sci. & Technol., Harbin, China
Abstract :
The gas outburst forecasts model is brought forward in this paper. Firstly, rough set requires discrimination data, considering distributed information of class, and continual condition attributes are discredited adopting information entropy theory. On the basis of that, redundancy attributes are eliminated using rough set reduction algorithm. Reduction attributes and rules are gained. Finally, through instances test the result indicates that forecasts model has higher exact ratio.
Keywords :
entropy; rough set theory; discrimination data; distributed information; gas outburst forecast model; gas outburst forecasting; information entropy theory; reduction attribute; redundancy attribute; rough set reduction algorithm; Biological system modeling; Data mining; Decision making; Fuel processing industries; Information entropy; Predictive models; Set theory; Discretization; Gas Outburst; Information Entropy; Routh Set;
Conference_Titel :
Genetic and Evolutionary Computing (ICGEC), 2010 Fourth International Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-1-4244-8891-9
Electronic_ISBN :
978-0-7695-4281-2
DOI :
10.1109/ICGEC.2010.9
