Volume 7 Number 10 (Oct. 2012)
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JSW 2012 Vol.7(10): 2241-2246 ISSN: 1796-217X
doi: 10.4304/jsw.7.10.2241-2246

Prediction of Water Inrush from Coal Floor Based on Small Sample Data Mining Technology and Realization Using MATLAB

Li Yang1, Li Song2, Jing Han3, and Jinkai Li4
1School of Economy and Management, Anhui University of Science & Technology, Huainan, Anhui, China
2School of Economics and Management, Anhui University of Science & Technology, Huainan, China, 232001
3Huainan Vocational & Technical College, Huainan, Anhui, china
4School of Economy and Management, Anhui University of Science & Technology, Huainan, Anhui, China

Abstract—For there are few samples of water inrush from coal floor, how to dig wider information under the circumstance of limited sample data is to improve the prediction accuracy of water inrush form coal floor. Therefore, prediction model of water inrush is established based on correlation analysis and support vector machine (SVM). Not only does the model simplify the influenced indexes to construct the index system of water inrush from coal floor, but also dig the value of sample data to solve the problem of small sample and nonlinear prediction. Through the empirical analysis, the model using MATLAB can accurately predict whether water inrush from coal floor occurs.

Index Terms—Small Sample; Support Vector Machine; Correlation Analysis; Prediction of Water Inrush; MATLAB

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Cite: Li Yang, Li Song, Jing Han, and Jinkai Li, "Prediction of Water Inrush from Coal Floor Based on Small Sample Data Mining Technology and Realization Using MATLAB," Journal of Software vol. 7, no. 10, pp. 2241-2246, 2012.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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