Application of bio and nature-inspired algorithms in agricultural engineering

C Maraveas, PG Asteris, KG Arvanitis… - … Methods in Engineering, 2023 - Springer
The article reviewed the four major Bioinspired intelligent algorithms for agricultural
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

AA Alabdullah, M Iqbal, M Zahid, K Khan… - … and Building Materials, 2022 - Elsevier
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 …

Predicting uniaxial compressive strength of rocks using ANN models: incorporating porosity, compressional wave velocity, and schmidt hammer data

PG Asteris, M Karoglou, AD Skentou, G Vasconcelos… - Ultrasonics, 2024 - Elsevier
The unconfined compressive strength (UCS) of intact rocks is crucial for engineering
applications, but traditional laboratory testing is often impractical, especially for historic …

Machine learning models for predicting the compressive strength of concrete containing nano silica

A Garg, P Aggarwal, Y Aggarwal… - Computers and …, 2022 - koreascience.kr
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 …

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
AR Ghanizadeh, A Delaram, P Fakharian… - Applied Sciences, 2022 - mdpi.com
The collapse settlement of granular soil, which brings about considerable deformations, is
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

S Ghani, S Kumari, S Ahmad - Arabian Journal for Science and …, 2022 - Springer
Researchers in the past have reported significant uncertainties involved in evaluating the
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

R Biswas, E Li, N Zhang, S Kumar, B Rai… - Construction and Building …, 2022 - Elsevier
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 …

Multi-expression programming based prediction of the seismic capacity of reinforced concrete rectangular columns

R Asghar, MF Javed, M Saqib, A Alaskar, M Ali… - … applications of artificial …, 2024 - Elsevier
This article presents an innovative artificial intelligence based multi-expression
programming approach to predict the seismic capacity of reinforced concrete rectangular …