35 Years of (AI) in geotechnical engineering: state of the art

AM Ebid - Geotechnical and Geological Engineering, 2021 - Springer
It was 35 years ago since the first usage of Artificial Intelligence (AI) technique in
geotechnical engineering, during those years many (AI) techniques were developed based …

Comparison of hybrid machine learning methods for the prediction of short-term meteorological droughts of Sakarya Meteorological Station in Turkey

H Citakoglu, Ö Coşkun - Environmental Science and Pollution Research, 2022 - Springer
Drought is a harmful natural disaster with various negative effects on many aspects of life. In
this research, short-term meteorological droughts were predicted with hybrid machine …

Modeling monthly reference evapotranspiration process in Turkey: application of machine learning methods

S Bayram, H Çıtakoğlu - Environmental Monitoring and Assessment, 2023 - Springer
In this study, the predictive power of three different machine learning (ML)-based
approaches, namely, multi-gene genetic programming (MGGP), M5 model trees (M5Tree) …

A review of machine learning approaches to soil temperature estimation

M Taheri, HK Schreiner, A Mohammadian, H Shirkhani… - Sustainability, 2023 - mdpi.com
Soil temperature is an essential factor for agricultural, meteorological, and hydrological
applications. Direct measurement, despite its high accuracy, is impractical on a large spatial …

[HTML][HTML] Measurement-based relationships between container ship operating parameters and fuel consumption

T Cepowski, A Drozd - Applied Energy, 2023 - Elsevier
Increases in fuel prices and the need to decrease emissions have made the optimization of
fuel consumption on ships more critical. Develo** a method to accurately estimate fuel …

Earth skin temperature long-term prediction using novel extended Kalman filter integrated with Artificial Intelligence models and information gain feature selection

M Jamei, M Karbasi, OA Alawi, HM Kamar… - … Informatics and Systems, 2022 - Elsevier
Predictions of Earth skin temperature (EST) can provide essential information for diverse
engineering applications such as energy harvesting and agriculture activities. Several …

Interpretation the influence of hydrometeorological variables on soil temperature prediction using the potential of deep learning model

S Elsayed, M Gupta… - Knowledge …, 2023 - … journals.publicknowledgeproject.org
The importance of soil temperature (ST) quantification can contribute to diverse ecological
modelling processes as well as for agricultural activities. Over the literature, it was evident …

Comparative analysis of machine learning models for predicting PM2. 5 concentrations using meteorological and chemical indicators

M Haseeb, Z Tahir, SA Mahmood, H Arif… - Journal of Atmospheric …, 2024 - Elsevier
Air pollution significantly impacts human health, causing numerous premature deaths,
particularly with the rise in PM 2.5 concentrations. Therefore, comparing different machine …

Comparative analysis of hybrid models of firefly optimization algorithm with support vector machines and multilayer perceptron for predicting soil temperature at …

S Shamshirband, F Esmaeilbeiki… - Engineering …, 2020 - Taylor & Francis
This research aims to model soil temperature (ST) using machine learning models of
multilayer perceptron (MLP) algorithm and support vector machine (SVM) in hybrid form with …

Buckling load estimation using multiple linear regression analysis and multigene genetic programming method in cantilever beams with transverse stiffeners

A Özbayrak, MK Ali, H Çıtakoğlu - Arabian Journal for Science and …, 2023 - Springer
Analytical methods cannot find the exact solution for inelastic lateral torsional buckling. This
study aims to develop innovative solutions by creating closed-form equations. A series of …