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Physics-informed neural networks with rational weighting for treating discontinuities in water flow prediction over irregular geometries
Physics-informed neural networks with rational weighting for treating discontinuities in water flow prediction over irregular geometries
Comprehensive Review of the Impact of Thermodynamic Inhibitors and the Predictive Power of Machine Learning Models on Hydrate Formation Pressure and Temperature
A new empirical model for prediction of jumbo drills' penetration rate in underground mines based on the rock mass characteristics
Prediction of jumbo drill penetration rate in underground mines using various machine learning approaches and traditional models
Comprehensive Review of the Impact of Thermodynamic Inhibitors and the Predictive Power of Machine Learning Models on Hydrate Formation Pressure and Temperature
Predicting soil chemical characteristics in the arid region of central Iran using remote sensing and machine learning models
A new empirical model for prediction of jumbo drills' penetration rate in underground mines based on the rock mass characteristics
Prediction of jumbo drill penetration rate in underground mines using various machine learning approaches and traditional models
Predicting soil chemical characteristics in the arid region of central Iran using remote sensing and machine learning models
Three-dimensional wake transition of rectangular cylinders and temporal prediction of flow patterns based on a machine learning algorithm
Physics-informed neural networks with rational weighting for treating discontinuities in water flow prediction over irregular geometries
Comparative analysis of machine learning models for predicting river water quality: a case study of the Zayandeh Rood River
N. Asadi
In situ synthesis of TiO2 nanofiller in preparation of carrageenan-based nanocomposites and its application in the adsorption of copper(ІI) from aqueous solution G Mohammadnezhad, P Moshiri, M Dinari, W Plass, Scientific reports Scientific reports 32294