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Predicting the Hairiness and Coefficient of Variation of Elastic Core-spun Yarns Produced on Sirofil-Spinning System using Artificial Neural Network
Predicting the Hairiness and Coefficient of Variation of Elastic Core-spun Yarns Produced on Sirofil-Spinning System using Artificial Neural Network
Spatial prediction of soil great groups by boosted regression trees using a limited point dataset in an arid region southeastern Iran
Spatial prediction of soil great groups by boosted regression trees using a limited point dataset in an arid region southeastern Iran
Prediction and assessment of drought effects on surface water quality using artificial neural networks case study of Zayandehrud River Iran
Wavelet neural network modeling in QSPR for prediction of solubility of 25 anthraquinone dyes at different temperatures and pressures in supercritical carbon dioxide
Wavelet neural network modeling in QSPR for prediction of solubility of 25 anthraquinone dyes at different temperatures and pressures in supercritical carbon dioxide
Comparing artificial neural network and multivariate linear regression models to predict soil organic carbon using digital terrain attributes
Predicting Mechanical Properties of Cold Rolled Low Carbon Steel Based on Magnetic Parameter Measurement using Artificial Neural Network
Predicting Mechanical Properties of Cold Rolled Low Carbon Steel Based on Magnetic Parameter Measurement using Artificial Neural Network
Predicting Radial and Tangential No-Load Air-Gap Flux Density in IPMSM Using a Novel Conformal Mapping and Lumped Parameter Model
A Comparative Analysis of Machine Learning Models for Predicting Groundwater and Surface Water in a Stressed Semi-Arid Watershed: The Khanmirza Case Study
Predicting Rock Hardness Using Measurement While Drilling (MWD) Data in a Case Study of Rotary Drilling in an Open-Pit Mine
A comparative analysis of machine learning models for predicting groundwater and surface water in a stressed semi-arid watershed: The Khanmirza case study
Integrating proximal sensing data (soil spectra and magnetic susceptibility) with the common covariates to predict soil carbon pools in semiarid regions