State-of-the-art review of machine learning and optimization algorithms applications in environmental effects of blasting
The technological difficulties related with blasting operations have become increasingly
significant. It is crucial to give due consideration to the evaluation of rock fragmentation and …
significant. It is crucial to give due consideration to the evaluation of rock fragmentation and …
Machine learning in coastal bridge hydrodynamics: a state-of-the-art review
Coastal bridges are vulnerable to complicated hydrodynamics induced by hostile natural
hazards, relevant research is thus required to ensure the safe operation of these critical …
hazards, relevant research is thus required to ensure the safe operation of these critical …
A new hybrid grey wolf optimizer-feature weighted-multiple kernel-support vector regression technique to predict TBM performance
Full-face tunnel boring machine (TBM) is a modern and efficient tunnel construction
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …
equipment. A reliable and accurate TBM performance (like penetration rate, PR) prediction …
Prediction of pile bearing capacity using XGBoost algorithm: modeling and performance evaluation
M Amjad, I Ahmad, M Ahmad, P Wróblewski… - Applied Sciences, 2022 - mdpi.com
The major criteria that control pile foundation design is pile bearing capacity (Pu). The load
bearing capacity of piles is affected by the various characteristics of soils and the …
bearing capacity of piles is affected by the various characteristics of soils and the …
Prediction of ground vibration induced by blasting operations through the use of the Bayesian Network and random forest models
The present study aims to compare the performance of two machine learning techniques
that can unveil the relationship between the input and target variables and predict the …
that can unveil the relationship between the input and target variables and predict the …
[HTML][HTML] Prediction of compaction parameters for fine-grained soil: Critical comparison of the deep learning and standalone models
A comparison between deep learning and standalone models in predicting the compaction
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …
parameters of soil is presented in this research. One hundred and ninety and fifty-three soil …
Multi-objective bat optimization for a biomass gasifier integrated energy system based on 4E analyses
An innovative biomass gasifier integrated plant was proposed for combined heating and
power production in the current paper. The plant consists of an s-CO 2 cycle, gasifier …
power production in the current paper. The plant consists of an s-CO 2 cycle, gasifier …
Prediction of ultimate bearing capacity of shallow foundations on cohesionless soil using hybrid lstm and rvm approaches: An extended investigation of …
This research presents the optimum performance model for predicting the shallow
foundation ultimate bearing capacity (UBC). Twenty-one models are employed, trained …
foundation ultimate bearing capacity (UBC). Twenty-one models are employed, trained …
Reinforced concrete deep beam shear strength capacity modelling using an integrative bio-inspired algorithm with an artificial intelligence model
G Zhang, ZH Ali, MS Aldlemy, MH Mussa… - Engineering with …, 2022 - Springer
The design and sustainability of reinforced concrete deep beam are still the main issues in
the sector of structural engineering despite the existence of modern advancements in this …
the sector of structural engineering despite the existence of modern advancements in this …
Short-term electrical load forecasting using hybrid model of manta ray foraging optimization and support vector regression
S Li, X Kong, L Yue, C Liu, MA Khan, Z Yang… - Journal of Cleaner …, 2023 - Elsevier
Demand prediction is playing a progressively important role in electricity management, and
is fundamental to the corresponding decision-making. Because of the high variability of the …
is fundamental to the corresponding decision-making. Because of the high variability of the …