Prediction of rapid chloride penetration resistance of metakaolin based high strength concrete using light GBM and XGBoost models by incorporating SHAP analysis
This study investigates the non-linear capabilities of two machine learning prediction
models, namely Light GBM and XGBoost, for predicting the values of Rapid Chloride …
models, namely Light GBM and XGBoost, for predicting the values of Rapid Chloride …
Economic dispatch optimization strategies and problem formulation: A comprehensive review
Economic Dispatch Problems (EDP) refer to the process of determining the power output of
generation units such that the electricity demand of the system is satisfied at a minimum cost …
generation units such that the electricity demand of the system is satisfied at a minimum cost …
Soft computing techniques for the prediction of concrete compressive strength using Non-Destructive tests
This study presents a comparative assessment of conventional soft computing techniques in
estimating the compressive strength (CS) of concrete utilizing two non-destructive tests …
estimating the compressive strength (CS) of concrete utilizing two non-destructive tests …
Predicting the thermal conductivity of soils using integrated approach of ANN and PSO with adaptive and time-varying acceleration coefficients
This study aims to propose hybrid adaptive neuro swarm intelligence (HANSI) techniques for
predicting the thermal conductivity of unsaturated soils. The novel contribution is made by …
predicting the thermal conductivity of unsaturated soils. The novel contribution is made by …
Consumers profiling based federated learning approach for energy load forecasting
Energy load estimation is critical for the smooth functioning of several activities, such as
reliable supply, reduced wastage, decision making and generation planning tasks. So far …
reliable supply, reduced wastage, decision making and generation planning tasks. So far …
Application of artificial intelligence techniques in slope stability analysis: a short review and future prospects
Artificial intelligence (AI) techniques have become a trusted methodology among
researchers in the recent decade for handling a variety of geotechnical and geological …
researchers in the recent decade for handling a variety of geotechnical and geological …
[HTML][HTML] Wavelet-based neural network with genetic algorithm optimization for generation prediction of PV plants
C Zhang, M Zhang - Energy Reports, 2022 - Elsevier
In order to solve the problem of uncertainty of photovoltaic power generation forecast, the
prediction accuracy of photovoltaic power station power generation is further improved. In …
prediction accuracy of photovoltaic power station power generation is further improved. In …
Prediction of the seismic effect on liquefaction behavior of fine-grained soils using artificial intelligence-based hybridized modeling
Researchers in the past have reported significant uncertainties involved in evaluating the
risk of soil liquefaction using deterministic approaches. Therefore, to improve the accuracy …
risk of soil liquefaction using deterministic approaches. Therefore, to improve the accuracy …
[HTML][HTML] Predicting and validating the load-settlement behavior of large-scale geosynthetic-reinforced soil abutments using hybrid intelligent modeling
Settlement prediction of geosynthetic-reinforced soil (GRS) abutments under service loading
conditions is an arduous and challenging task for practicing geotechnical/civil engineers …
conditions is an arduous and challenging task for practicing geotechnical/civil engineers …
[HTML][HTML] Novel integration of extreme learning machine and improved Harris hawks optimization with particle swarm optimization-based mutation for predicting soil …
The study proposes an improved Harris hawks optimization (IHHO) algorithm by integrating
the standard Harris hawks optimization (HHO) algorithm and mutation-based search …
the standard Harris hawks optimization (HHO) algorithm and mutation-based search …