دوره 10، شماره 3 - ( 3-1399 )                   جلد 10 شماره 3 صفحات 492-481 | برگشت به فهرست نسخه ها

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Fattahi H. ANALYSIS OF ROCK MASS BOREABILITY IN MECHANICAL TUNNELING USING RELEVANCE VECTOR REGRESSION OPTIMIZED BY DOLPHIN ECHOLOCATION ALGORITHM. IJOCE 2020; 10 (3) :481-492
URL: http://ijoce.iust.ac.ir/article-1-447-fa.html
ANALYSIS OF ROCK MASS BOREABILITY IN MECHANICAL TUNNELING USING RELEVANCE VECTOR REGRESSION OPTIMIZED BY DOLPHIN ECHOLOCATION ALGORITHM. عنوان نشریه. 1399; 10 (3) :481-492

URL: http://ijoce.iust.ac.ir/article-1-447-fa.html


چکیده:   (10821 مشاهده)
During project planning, the prediction of TBM performance is a key factor for selection of tunneling methods and preparation of project schedules. During the construction, TBM performance need to be evaluated based on the encountered rock mass conditions. In this paper, the model based on a relevance vector regression (RVR) optimized by dolphin echolocation algorithm (DEA) for prediction of specific rock mass boreability index (SRMBI) is proposed. The DEA is combined with the RVR for determining the optimal value of its user-defined parameters. The optimized RVR by DEA was employed to available data given in the open source literature. In this model, rock mass uniaxial compressive strength, brittleness index (Bi), volumetric joint account (Jv), and joint orientation (Jo) were used as the input, while the SRMBI was the output parameter. The performances of the suggested predictive model were tested according to two performance indices, i.e., mean square error and determination coefficient. The results show that the RVR- DEA model can be successfully utilized for estimation of the SRMBI in mechanical tunneling.
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نوع مطالعه: پژوهشي | موضوع مقاله: Applications
دریافت: 1399/4/24 | پذیرش: 1399/4/24 | انتشار: 1399/4/24

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