Predicting tensile strength of rocks from physical properties based on support vector regression optimized by cultural algorithm | ||
| Journal of Mining and Environment | ||
| مقاله 11، دوره 8، شماره 3، مهر 2017، صفحه 467-474 اصل مقاله (723.24 K) | ||
| نوع مقاله: Case Study | ||
| شناسه دیجیتال (DOI): 10.22044/jme.2016.824 | ||
| نویسندگان | ||
| H. Fattahi1؛ N. Babanouri* 2 | ||
| 1Department of Mining Engineering, Arak University of Technology, Arak, Iran | ||
| 2Department of Mining Engineering, Hamedan University of Technology, Hamedan, Iran | ||
| چکیده | ||
| The tensile strength (TS) of rocks is an important parameter in the design of a variety of engineering structures such as the surface and underground mines, dam foundations, types of tunnels and excavations, and oil wells. In addition, the physical properties of a rock are intrinsic characteristics, which influence its mechanical behavior at a fundamental level. In this paper, a new approach combining the support vector regression (SVR) with a cultural algorithm (CA) is presented in order to predict TS of rocks from their physical properties. CA is used to determine the optimal value of the SVR controlling the parameters. A dataset including 29 data points was used in this study, in which 20 data points (70%) were considered for constructing the model and the remaining ones (9 data points) were used to evaluate the degree of accuracy and robustness. The results obtained show that the SVR optimized by the CA model can be successfully used to predict TS. | ||
| کلیدواژهها | ||
| Tensile Strength (TS) of Rocks؛ Support Vector Regression (SVR)؛ Cultural Algorithm (CA)؛ Physical Properties | ||
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