Prediction of Gas Emission Quantity Based on Least Square Support Vector Machine

Jun Wei Yuan; Kai Wang; Xiao Gai Jiang

doi:10.4028/www.scientific.net/AMR.619.572

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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 619Prediction of Gas Emission Quantity Based on Least...

Prediction of Gas Emission Quantity Based on Least Square Support Vector Machine

Abstract:

Gas emission quantity has been affected by several natural factors and development of technology, which is a nonlinear and high-dimension problem. By using least square support vector machine (LSSVM), gas emission quantity in mined- out working face has been calculated, and then it has been compared and analyzed with measurement. Besides, gas emission quantity in pre-mining has been predicted. The results indicate that the higher the prediction accuracy of LSSVM is, the stronger the generalization is.

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Periodical:

Advanced Materials Research (Volume 619)

Pages:

572-576

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.619.572

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Online since:

December 2012

Authors:

Jun Wei Yuan, Kai Wang, Xiao Gai Jiang

Keywords:

Error Analysis, Gas Emission Quantity, Least Squares Support Vector Machines (Ls-SVM), Prediction

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