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Application of bio and nature-inspired algorithms in agricultural engineering
The article reviewed the four major Bioinspired intelligent algorithms for agricultural
applications, namely ecological, swarm-intelligence-based, ecology-based, and multi …
applications, namely ecological, swarm-intelligence-based, ecology-based, and multi …
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 …
Predicting uniaxial compressive strength of rocks using ANN models: incorporating porosity, compressional wave velocity, and schmidt hammer data
The unconfined compressive strength (UCS) of intact rocks is crucial for engineering
applications, but traditional laboratory testing is often impractical, especially for historic …
applications, but traditional laboratory testing is often impractical, especially for historic …
Machine learning models for predicting the compressive strength of concrete containing nano silica
Experimentally predicting the compressive strength (CS) of concrete (for a mix design) is a
time-consuming and laborious process. The present study aims to propose surrogate …
time-consuming and laborious process. The present study aims to propose surrogate …
Research progress of soil thermal conductivity and its predictive models
R ** predictive models of collapse settlement and coefficient of stress release of sandy-gravel soil via evolutionary polynomial regression
The collapse settlement of granular soil, which brings about considerable deformations, is
an important issue in geotechnical engineering. Several factors are involved in this …
an important issue in geotechnical engineering. Several factors are involved in this …
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 …
Development of hybrid models using metaheuristic optimization techniques to predict the carbonation depth of fly ash concrete
Carbonation is one of the utmost serious issues affecting the long-term durability of
reinforced concrete. When H 2 O is present, a reaction between CO 2 gas and Ca (OH) 2 …
reinforced concrete. When H 2 O is present, a reaction between CO 2 gas and Ca (OH) 2 …
Multi-expression programming based prediction of the seismic capacity of reinforced concrete rectangular columns
This article presents an innovative artificial intelligence based multi-expression
programming approach to predict the seismic capacity of reinforced concrete rectangular …
programming approach to predict the seismic capacity of reinforced concrete rectangular …