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A Comparative Analysis of Machine Learning Models for Predicting Groundwater and Surface Water in a Stressed Semi-Arid Watershed: The Khanmirza Case Study
A comparative analysis of machine learning models for predicting groundwater and surface water in a stressed semi-arid watershed: The Khanmirza case study
Refereed Journal Papers
Zahra Shafee Falavarjani
Preparation and characterization of optically active poly (amide-imide)/TiO2 bionanocomposites containing Ntrimellitylimido-L- isoleucine linkages: Using ionic liquid and ultrasonic irradiation
Integrating Land Use Impact Model with Bayesian Belief Networks to Map and Assess the Risk of Soil Erosion in Karchambooy Catchment, Isfahan
Production of NiAl-layered double hydroxide intercalated with bio-safe amino acid containing organic dianion and its utilization in formation of LDH/poly(amide-imide) nanocomposites
A Computational study on robust prediction of transition point over NACA۰۰۱۲ aerofoil surfaces from laminar to turbulent flows
Shahbaz Mehrabi
علاقمندی‌های پژوهشی
Comparison of Infinite Fracture Model (IFM) and Discrete Fracture Network (DFN) for Estimating the Volume of In-Situ Blocks in Dimension Stone Mines with a Focus on UAV …
Mathematical Analysis II [Multivariable Analysis] (Undergraduate Course)
Neda Abbasi
FRASCATI-DAFNE-DEAR (Frascati)
Supervisor