期刊
MATHEMATICAL PROBLEMS IN ENGINEERING
卷 2013, 期 -, 页码 -出版社
HINDAWI LTD
DOI: 10.1155/2013/579693
关键词
-
资金
- National Natural Science Foundation Project of NSFC (NSFC) [50804061]
- Chongqing Education Administration Program Foundation of China [KJ120514, KJ110513]
- Natural Science Foundation Project of CQ CSTC [2012BB3725]
- Foundation for University Youth Key Teacher of Chongqing, Outstanding Achievement Transformation Project of CQ CQJW [KJzh10207]
It is well known that mine gas gushing forecasting is very significant to ensure the safety of mining. A wavelet-based robust relevance vector machine based on sensor data scheduling control for modeling mine gas gushing forecasting is presented in the paper. Morlet wavelet function can be used as the kernel function of robust relevance vector machine. Mean percentage error has been used to measure the performance of the proposed method in this study. As the mean prediction error of mine gas gushing of the WRRVM model is less than 1.5%, and the mean prediction error of mine gas gushing of the RVM model is more than 2.5%, it can be seen that the prediction accuracy for mine gas gushing of the WRRVM model is better than that of the RVM model.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据