Performance evaluation of hybrid WOA-XGBoost, GWO-XGBoost and BO-XGBoost models to predict blast-induced ground vibration

Y Qiu, J Zhou, M Khandelwal, H Yang, P Yang… - Engineering with …, 2022 - Springer
Accurate prediction of ground vibration caused by blasting has always been a significant
issue in the mining industry. Ground vibration caused by blasting is a harmful phenomenon …

[HTML][HTML] Slope stability prediction using ensemble learning techniques: A case study in Yunyang County, Chongqing, China

W Zhang, H Li, L Han, L Chen, L Wang - Journal of Rock Mechanics and …, 2022 - Elsevier
Slope stability prediction plays a significant role in landslide disaster prevention and
mitigation. This study develops an ensemble learning-based method to predict the slope …

A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength

DJ Armaghani, PG Asteris - Neural Computing and Applications, 2021 - Springer
Despite the extensive use of mortars materials in constructions over the last decades, there
is not yet a reliable and robust method, available in the literature, which can estimate its …

Optimization of support vector machine through the use of metaheuristic algorithms in forecasting TBM advance rate

J Zhou, Y Qiu, S Zhu, DJ Armaghani, C Li… - … Applications of Artificial …, 2021 - Elsevier
The advance rate (AR) of a tunnel boring machine (TBM) in hard rock condition is a key
parameter for the successful accomplishment of a tunneling project, and the proper and …

Ensemble deep learning-based models to predict the resilient modulus of modified base materials subjected to wet-dry cycles

M Esmaeili-Falak, RS Benemaran - Geomechanics and …, 2023 - koreascience.kr
The resilient modulus (MR) of various pavement materials plays a significant role in the
pavement design by a mechanistic-empirical method. The MR determination is done by …

Predicting resilient modulus of flexible pavement foundation using extreme gradient boosting based optimised models

R Sarkhani Benemaran, M Esmaeili-Falak… - International Journal of …, 2023 - Taylor & Francis
Resilient modulus (MR) plays the most critical role in the evaluation and design of flexible
pavement foundations. MR is utilised as the principal parameter for representing stiffness …

[HTML][HTML] Predicting TBM penetration rate in hard rock condition: A comparative study among six XGB-based metaheuristic techniques

J Zhou, Y Qiu, DJ Armaghani, W Zhang, C Li, S Zhu… - Geoscience …, 2021 - Elsevier
A reliable and accurate prediction of the tunnel boring machine (TBM) performance can
assist in minimizing the relevant risks of high capital costs and in scheduling tunneling …

[HTML][HTML] Stacking integration algorithm based on CNN-BiLSTM-Attention with XGBoost for short-term electricity load forecasting

S Luo, B Wang, Q Gao, Y Wang, X Pang - Energy Reports, 2024 - Elsevier
Improving the accuracy of electric load forecasting is critical for grid stability, industrial
production, and residents' daily lives. Traditional short-term load forecasting methods often …

Recent advances in 3D slope stability analysis: a detailed review

S Kumar, SS Choudhary, A Burman - Modeling Earth Systems and …, 2023 - Springer
Regarding the geotechnical aspects, it is very important to correctly estimate a slope's safety
factor against failure. Slope failures, in general, cost a lot of money, hinder transportation …

A novel artificial intelligence technique to predict compressive strength of recycled aggregate concrete using ICA-XGBoost model

J Duan, PG Asteris, H Nguyen, XN Bui… - Engineering with …, 2021 - Springer
Recycled aggregate concrete is used as an alternative material in construction engineering,
aiming to environmental protection and sustainable development. However, the …