Yifan Huang¹, Zikang Zhou^1,2, Mingyu Li¹, Xuedong Luo^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3147-3165, 2024, DOI:10.32604/cmes.2024.045947

Abstract Accurately estimating blasting vibration during rock blasting is the foundation of blasting vibration management. In this study, Tuna Swarm Optimization (TSO), Whale Optimization Algorithm (WOA), and Cuckoo Search (CS) were used to optimize two hyperparameters in support vector regression (SVR). Based on these methods, three hybrid models to predict peak particle velocity (PPV) for bench blasting were developed. Eighty-eight samples were collected to establish the PPV database, eight initial blasting parameters were chosen as input parameters for the prediction model, and the PPV was the output parameter. As predictive performance evaluation indicators, the coefficient of determination (R²), root mean square… More >

Quang-Hieu Tran^1,2,*, Hoang Nguyen^1,2, Xuan-Nam Bui^1,2

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2227-2246, 2023, DOI:10.32604/cmes.2022.021893

Abstract This study considered and predicted blast-induced ground vibration (PPV) in open-pit mines using bagging and sibling techniques under the rigorous combination of machine learning algorithms. Accordingly, four machine learning algorithms, including support vector regression (SVR), extra trees (ExTree), K-nearest neighbors (KNN), and decision tree regression (DTR), were used as the base models for the purposes of combination and PPV initial prediction. The bagging regressor (BA) was then applied to combine these base models with the efforts of variance reduction, overfitting elimination, and generating more robust predictive models, abbreviated as BA-ExTree, BAKNN, BA-SVR, and BA-DTR. It is emphasized that the ExTree… More >

Yongheng Ku¹, Jinguang Zhang^2,3, Zhenyu Wang^3,4, Youxin Li^3,5, Haowei Yao^3,5,*

FDMP-Fluid Dynamics & Materials Processing, Vol.17, No.6, pp. 1077-1090, 2021, DOI:10.32604/fdmp.2021.015779

Abstract In order to study the extinguishing performance of high-pressure-water-mist-based systems on the fires originating from power transformers the PyroSim software is used. Different particle velocities and flow rates are considered. The evolution laws of temperature around transformer, flue gas concentration and upper layer temperature of flue gas are analyzed under different boundary conditions. It is shown that the higher the particle velocity is, the lower the smoke concentration is, the better the cooling effect on the upper layer temperature of flue gas layer is, the larger the flow rate is and the better the cooling effect is. More >