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A New Approach for Predicting the Pressure Drop in Various Types of Metal Foams Using a Combination of CFD and Machine Learning Regression Models
Comparison of artificial neural network and multiple linear regression efficiency for predicting soil salinity in Yazd-Ardekan plain central Iran
Feeding heat-treated soybean to mid-lactation Holstein cows Production performance, predicted efficiency of nitrogen utilization, and blood metabolites
Feeding heat-treated soybean to mid-lactation Holstein cows Production performance, predicted efficiency of nitrogen utilization, and blood metabolites
Developing a new rock classification based on the abrasiveness hardness and toughness of rocks and PA for the prediction of hard dimension stone sawability in quarrying
Predicting the Building Stone Cutting Rate Based on Rock Properties and Device Pullback Amperage in Quarries Using M5P Model Tree
EXPERIMENTAL AND NUMERICAL INVESTIGATION OF THE DEEP DRAWING PROCESS FOR AN AUTOMOBILE PANEL AND PREDICTION OF APPROPRIATE AMOUNT OF PARAMETERS BY MULTI-LAYER NEURAL NETWORK
Artificial Neural Network Models for Production of Nano-Grained Structure in AISI 304L Stainless Steel by Predicting Thermo-Mechanical Parameters
Artificial Neural Network Models for Production of Nano-Grained Structure in AISI 304L Stainless Steel by Predicting Thermo-Mechanical Parameters
Prediction of solubility for polycyclic aromatic hydrocarbons in supercritical carbon dioxide using wavelet neural networks in quantitative structure property relationship
Application of QSPR for prediction of percent conversion of esterification reactions in supercritical carbon dioxide using least squares support vector regression
Application of QSPR for prediction of percent conversion of esterification reactions in supercritical carbon dioxide using least squares support vector regression
Predicting Tensile Properties of UV Degraded Nylon66/Polyester Woven Fabric Using Regression and Artificial Neural Network Models
Predicting Tensile Properties of UV Degraded Nylon66/Polyester Woven Fabric Using Regression and Artificial Neural Network Models
Improving the Prediction of Part Thickness in Superplastic Forming Process of Ti 6Al 4V Alloy Using an Appropriate Constitutive Equation