M
Mohammad Isazadeh
Researcher at University of Tabriz
Publications - 9
Citations - 380
Mohammad Isazadeh is an academic researcher from University of Tabriz. The author has contributed to research in topics: Aquifer & Normalization (statistics). The author has an hindex of 7, co-authored 9 publications receiving 222 citations.
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A comparative study of artificial neural network (MLP, RBF) and support vector machine models for river flow prediction
TL;DR: In this article, the applicability of multilayer perceptron (MLP), radial basis function (RBF) and support vector machine (SVM) models for prediction of river flow time series was investigated.
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Groundwater quality assessment for sustainable drinking and irrigation
Esmaeil Asadi,Mohammad Isazadeh,Saeed Samadianfard,Mohammad Firuz Ramli,Amir Mosavi,Amir Mosavi,Amir Mosavi,Narjes Nabipour,Shahaboddin Shamshirband,Éva Hajnal,Kwok Wing Chau +10 more
TL;DR: A groundwater compatibility study was conducted by analyzing Electrical conductivity (EC), total dissolved solids (TDS), Chloride (Cl), Calcium (Ca), Magnesium (Mg), Sodium (Na), Potassium (K), Sulfate (SO4), Total hardness (TH), Bicarbonate (HCO3), pH, carbonate (CO3) and Sodium Adsorption Ratio (SAR) obtained from 39 wells in the time period from 2003 to 2014 as discussed by the authors.
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Support vector machines and feed-forward neural networks for spatial modeling of groundwater qualitative parameters
TL;DR: In this article, the spatial variability of three groundwater qualitative parameters in Guilan Province, northern Iran, using artificial neural networks (ANNs) and support vector machines (SVMs) was modeled using data collected from 140 observation wells for the years 2002-2014.
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New input selection procedure for machine learning methods in estimating daily global solar radiation
TL;DR: In this article, a new input selection method, procrustes analysis (PA), was implemented and compared with gamma test (GT) for estimating daily global solar radiation (Rs).
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Evaluation of geostatistical techniques and their hybrid in modelling of groundwater quality index in the Marand Plain in Iran
TL;DR: The results of modeling the WQI index based on IDW, kriging, cokriged, GWR, and hybrid methods showed that the best estimate was obtained by using hybrid GWR-kriging method with three input parameters of land slope, groundwater table, and groundwater transmissibility.