Comparative study of multiple machine learning algorithms for risk level prediction in goaf

Evaluating the effect of tissue stimulation at different frequencies on breast lesion classification based on nonlinear features using a novel radio frequency time series approach

“…The evaluation of the proposed system's performance encompassed seven parameters: accuracy, recall, specificity, precision or positive predictive value (PPV), negative predictive value (NPV), F score, and kappa which are defined as follows: where TP, TN, FP, and FN denote true positive, true negative, false positive, and false negative, respectively [ 67 ]. The kappa coefficient is an important index to evaluate the classification model [ 68 ]. Kappa can be calculated from a confusion matrix as: where P o and P e obtained from: …”

Stability mechanism and countermeasure of the solid coal rib in deep gob-side entry retaining: Insights from theoretical analysis numerical simulation

“…The implementation of gob-side entry retaining (GER) technology provides technical support for the successful execution of deep continuous pressure relief mining and deep coal and gas mining. It achieves this by reducing the necessity for extensive roadway excavation, mitigating mining tension, enhancing resource recovery efficiency, eliminating stress concentration on coal pillars, and addressing the issue of gas accumulation in upper corners [ [1] , [2] , [3] , [4] , [5] , [6] ]. Over time, GER technology has been progressively applied across various coal seam thicknesses - from thin seams (less than 1.3 m) [ [7] , [8] , [9] ], medium-thick seams (1.3 m–3.5 m) [ [10] , [11] , [12] ], fully mechanized thick seams (more than 3.5 m) [ [13] , [14] , [15] ], to even fully mechanized top coal caving mining operations [ 16 , 17 ].…”