دانلود مقاله ISI انگلیسی شماره 24325
عنوان فارسی مقاله

بررسی ضخامت سنگ منطقه شکسته برای خطوط جاده عمیق با استفاده از SVM ها غیر خطی و چند مدل رگرسیون خطی

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
24325 2011 10 صفحه PDF سفارش دهید محاسبه نشده
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Evaluating the Thickness of Broken Rock Zone for Deep Roadways using Nonlinear SVMs and Multiple Linear Regression Model
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Procedia Engineering, Volume 26, 2011, Pages 972–981

کلمات کلیدی
() () - () - سنگ شکسته منطقه (بعرض) - سنگ های اطراف - ماشین بردار پشتیبانی ( ها) - تجزیه و تحلیل چند رگرسیون خطی () -
پیش نمایش مقاله
پیش نمایش مقاله بررسی ضخامت سنگ منطقه شکسته برای خطوط جاده عمیق با استفاده از SVM ها غیر خطی و چند مدل رگرسیون خطی

چکیده انگلیسی

Since the traditional methods to estimation of the thickness of broken rock zone (BRZ) are usually difficult, expensive and not feasible in many cases, the development of some predictive models for the thickness of broken rock zone (BRZ) for deep roadways will be useful. To describe the complex relationship between geological factors and BRZ, a nonlinear model-based support vector machines (SVMs) regression analysis was applied on the data pertaining to China mine to develop some predictive models for the thickness of BRZ for deep roadways from the indirect methods in this study. The type of kernel function was Radial basis function (RBF). 132 samples were trained by proposed models; the other 10 samples that were not used for training were used to validate the trained models. The correlation coefficients of SVMs model for predicting the thickness of BRZ is more than 0.90. For the same two similarity groups, the developed SVMs model was also compared with the multiple linear regression analysis (MLRA) model and measured data. As a result of SVMs analysis, a very good model was derived for BRZ estimation. It was shown that SVMs models were more reliable and precise than the regression models. Concluding remark is that the thickness of BRZ values of deep roadways can reliably be estimated from the indirect methods using SVMs analysis.

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