Predicting ground vibration during rock blasting using relevance vector machine improved with dual kernels and metaheuristic algorithms

Y Fissha, J Khatti, H Ikeda, KS Grover, N Owada… - Scientific Reports, 2024 - nature.com
The ground vibration caused by rock blasting is an extremely hazardous outcome of the
blasting operation. Blasting activity has detrimental effects on both the ecology and the …

Towards designing durable sculptural elements: Ensemble learning in predicting compressive strength of fiber-reinforced nano-silica modified concrete

R Wang, J Zhang, Y Lu, J Huang - Buildings, 2024 - mdpi.com
Fiber-reinforced nano-silica concrete (FrRNSC) was applied to a concrete sculpture to
address the issue of brittle fracture, and the primary objective of this study was to explore the …

Prediction of compressive strength of geopolymer concrete landscape design: Application of the novel hybrid RF–GWO–XGBoost algorithm

J Zhang, R Wang, Y Lu, J Huang - Buildings, 2024 - mdpi.com
Landscape geopolymer concrete (GePoCo) with environmentally friendly production
methods not only has a stable structure but can also effectively reduce environmental …

Hybrid ensemble paradigms for estimating tunnel boring machine penetration rate for the 10-km long Bahce-Nurdagi twin tunnels

A Bardhan, NT Ozcan, PG Asteris… - Engineering Applications of …, 2024 - Elsevier
This study presents a novel hybrid ensemble strategy based on an inputs-outputs
amalgamation technique for estimating the rate of penetration (ROP) of tunnel boring …

Mechanical framework for geopolymer gels construction: an optimized LSTM technique to predict compressive strength of fly ash-based geopolymer gels concrete

X Shi, S Chen, Q Wang, Y Lu, S Ren, J Huang - Gels, 2024 - mdpi.com
As an environmentally responsible alternative to conventional concrete, geopolymer
concrete recycles previously used resources to prepare the cementitious component of the …

Development of mathematically motivated artificial intelligence models for the prediction of carbonate rock lime saturation factor for cement production

BO Taiwo, NM Shahani, A Omosebi, OB Samson… - … Applications of Artificial …, 2024 - Elsevier
Predicting the cement lime saturation factor (LSF) is vital in cement production as it
determines the optimal ratio of lime to other components. This factor affects the quality and …

[HTML][HTML] Data-Driven Optimised XGBoost for Predicting the performance of Axial load bearing capacity of fully Cementitious Grouted Rock Bolting systems

B Jodeiri Shokri, A Mirzaghorbanali, K McDougall… - Applied Sciences, 2024 - mdpi.com
This article investigates the application of eXtreme gradient boosting (XGBoost) and hybrid
metaheuristics optimisation techniques to predict the axial load bearing capacity of fully …

Enhancing the exploitation of natural resources for green energy: An application of LSTM-based meta-model for aluminum prices forecasting

MO Esangbedo, BO Taiwo, HH Abbas, S Hosseini… - Resources Policy, 2024 - Elsevier
Efficient resource allocation for electric car production can be achieved by anticipating
aluminum future pricing. For the electric car sector to maintain a steady supply chain …

Boosting-based ensemble machine learning models for predicting unconfined compressive strength of geopolymer stabilized clayey soil

GMS Abdullah, M Ahmad, M Babur, MU Badshah… - Scientific Reports, 2024 - nature.com
The present research employs new boosting-based ensemble machine learning models ie,
gradient boosting (GB) and adaptive boosting (AdaBoost) to predict the unconfined …

Prediction of uniaxial strength of rocks using relevance vector machine improved with dual kernels and metaheuristic algorithms

J Khatti, KS Grover - Rock Mechanics and Rock Engineering, 2024 - Springer
The uniaxial compressive strength (UCS) is an essential parameter to study rock
characteristics, determined by direct and indirect methods. However, the direct methods of …