This paper proposes a feature selection method based on a hybrid optimization algorithm that combines the Golden Jackal Optimization (GJO) and Grey Wolf Optimizer (GWO). The primary objective of this method is to create an effective data dimensionality reduction technique for eliminating redundant, irrelevant, and noisy features within high-dimensional datasets. Drawing inspiration from the Chinese idiom “Chai Lang Hu Bao,” hybrid algorithm mechanisms, and cooperative behaviors observed in natural animal populations, we amalgamate the GWO algorithm, the Lagrange interpolation method, and the GJO algorithm to propose the multi-strategy fusion GJO-GWO algorithm. In Case 1, the GJO-GWO algorithm addressed eight complex benchmark functions. In Case 2, GJO-GWO was utilized to tackle ten feature selection problems. Experimental results consistently demonstrate that under identical experimental conditions, whether solving complex benchmark functions or addressing feature selection problems, GJO-GWO exhibits smaller means, lower standard deviations, higher classification accuracy, and reduced execution times. These findings affirm the superior optimization performance, classification accuracy, and stability of the GJO-GWO algorithm.

Coal seam mining causes movement and deformation of the overlying rock mass and ground surface, directly resulting in serious damage to the surface construction facilities. To investigate the deformation mechanism and characteristics of the overlying rock mass, three-dimensional numerical simulation and model test are carried out on an open-pit mine slope. The results show that the sliding instability characteristics of the slope can be identified based on the numerical analysis. Coal mining affects on the deformation characteristics of the overlying rock mass near the inner dump. The closer to the slope boundary, the greater the subsidence of overlying rock mass. The maximum displacement occurs near the inner dump. The slope mining has great influence on the deformation characteristics of inner dump. Moreover, the damage process of overlying rock mass can be further studied via the model test. After coal seams mining out, the overlying rock mass occurs overall settlement failure. There is a large difference between the lower end side of working face and the upper end side at the caving angle of roof. This work can provide a basis for the safe operation of coal mine disaster prevention and mitigation.

Journal of Industrial and Intelligent Information

In view of the inclined occurrence of coal seam in Heishan open-pit coal mine, in the longitudinal exploitation process of the first mining area, the height of the slope at the west end is increasing, and the occurrence of weak interlayer in the slope is in production. The failure mechanism and stability of the end slope of the inclined composite coal seam, which is typical of the West end slope of Heishan open-pit mine, are studied by means of field investigation, theoretical analysis, limit equilibrium analysis, and numerical simulation. The factors affecting the stability of the western side slope and the potential landslide mode are analyzed. The residual thrust method and simplified Bishop method were used to study the stability of two potential landslide modes on the western slope, and the landslide mode, final slope angle, and slope morphology were determined. FLAC^3D was used to simulate the western end of the slope, reveal its landslide mechanism, and clarify the evolution law of the slope rock mass displacement. The results show that the landslide mode at the west end of the first mining area is the combined sliding mode of cutting and bedding. With the decrease of longitudinal mining depth, the final slope angle functions from 40° to 37°. The stress and strain are concentrated at the weak layer of the coal floor of the western side slope 13-2 and at the foot of the slope. Meanwhile, the failure also occurs inside the slope. The internal cracks connect through the weak layer of the coal floor and slide along the weak layer of the coal floor 13-2. The displacement evolution law of the slope monitoring point shows that the deformation of the slope is mainly horizontal displacement, the maximum displacement deformation is at the foot of the slope, and the degree of displacement deformation of the slope surface is obviously greater than that of the inside of the slope.

At present, there are limited empirical formulas for recovery factor estimation of carbonate reservoirs in the early stage of development. An improved recovery factor estimation method is established in this paper combining with displacement efficiency, sweep coefficient, well pattern coefficient, utilization factor, and reservoir connectivity coefficient. Among them, the utilization factor and connectivity coefficient is firstly proposed and established by derivation and reservoir simulation considering the characteristics of low-permeability carbonate reservoirs. The method is applied to M oilfield, and the estimation results are compared with other empirical formulas and field development calibration results, which shows good estimation accuracy.