کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
294901 | 511500 | 2009 | 5 صفحه PDF | دانلود رایگان |
Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions. The Support Vector Machine (SVM) is a new machine learning algorithm that has excellent properties. The least squares support vector machine (LS-SVM) algorithm is an improved algorithm of SVM. But the common LS-SVM algorithm, used directly in safety predictions, has some problems. We have first studied gas prediction problems and the basic theory of LS-SVM. Given these problems, we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm, based on LS-SVM. Finally, given our observed data, we used the on-line algorithm to predict gas emissions and used other related algorithm to compare its performance. The simulation results have verified the validity of the new algorithm.
Journal: Mining Science and Technology (China) - Volume 19, Issue 2, March 2009, Pages 194-198