Evaluation of a machine-based learning method to estimate the rate of nitrate penetration and groundwater contamination

AM Rokhshad, A Khashei Siuki… - Arabian Journal of …, 2021 - Springer
Groundwater is among the most important water resources around the globe. However, their
contaminations are more difficult, costly, and time-consuming to detect and control than …

The impact of climate change on reference evapotranspiration in Mazandaran Province

A Babolhekami, MA Gholami Sefidkouhi… - Iranian journal of soil …, 2020 - ijswr.ut.ac.ir
Greenhouse gas emissions cause warming and impacting climate components and
consequently affecting water demand in agricultural sector. This study aimed to identify the …

Performance Comparison of statistical, fuzzy and perceptron neural network models in forecasting dust storms in critical regions in Iran

M Ansari Ghojghar, M Pourgholam-Amiji… - Iranian Journal of Soil …, 2020 - ijswr.ut.ac.ir
Different regions have different potentials in dust release, and the increase in dust storms
indicates the dominance of the desert ecosystem in each region. Prediction of the …

Estimation of the local scour from a cylindrical bridge pier using a compilation wavelet model and artificial neural network

M Seifollahi, F Kalateh, R Daneshfaraz… - Journal of Hydraulic …, 2021 - jhs.scu.ac.ir
In the present study, an artificial neural network and its combination with wavelet theory are
used as the computational tool to predict the depth of local scouring from the bridge pier …

Evaluation of the effect of scenarios in the 6th report of IPCC on the prediction groundwater level using the non-linear model of the input-output time series

F Niroumand Fard, A Khashei Siuki… - Environmental …, 2023 - Springer
Due to the increase in greenhouse gases, water and climate crises, increasing population,
and decreasing water resources, accurately predicting the changes in the GWL is essential …

[PDF][PDF] Assessing the impact of climate change on drought and forecasting Neka river basin runoff in future periods

A Babolhakami, MA Gholami Sefidkouhi… - Iranian journal of …, 2020 - ije.ut.ac.ir
Several studies have shown that climate change will have severe impacts on available
water resources worldwide. Due to the effect of climate change on droughts and river flow, it …

Performance Evaluation of Genetic Algorithm and GA-SA Hybrid Method in Forecasting Dust Storms (Case Study: Khuzestan Province)

M Ansari Ghojghar, M Pourgholam-Amiji… - Iranian Journal of Soil …, 2020 - ijswr.ut.ac.ir
The increase in dust storms occurrence in recent years in southwestern Iran, especially in
Khuzestan province, and consequently the decrease in air quality in these areas, has …

[PDF][PDF] Introducing a nonlinear model based on hybrid machine learning for modeling and prediction of precipitation and comparison with SDSM method (Case study …

MV Anaraki, SF Mousavi, S Farzin… - Iranian Journal of Soil …, 2020 - researchgate.net
In the present study, a nonlinear hybrid model, based on multivariate adaptive regression
splines (MARS), artificial neural networks (ANN) and K-nearest neighbor (KNN) has been …

[PDF][PDF] Uncertainty analysis of water distribution planning in mian-ab irrigation network in shooshtar plain: application of genetic algorithm and simulated annealing

S Khoshnavaz - Iranian Journal of Soil and Water Research, 2020 - journals.ut.ac.ir
Allocated water for agricultural crops in a crop** pattern in different regions and seasons
is faced with much variation. Therefore, the cultivation of each crop is subject to climatic …

مقایسه کارایی شبکه‌های عصبی آماری، فازی و پرسپترونی در پیش‌بینی طوفان‌های گردوغبار در نواحی بحرانی کشور

انصاری قوجقار, پورغلام آمیجی, بذرافشان, لیاقت… - تحقیقات آب و خاک …, 2020‎ - ijswr.ut.ac.ir
مناطق مختلف، استعدادهای متفاوتی در انتشار گردوغبار دارند و افزایش طوفان‌های گردوغبار
نشان‌دهنده حاکمیت اکوسیستم بیابانی در هر منطقه است. درک صحیح وقوع طوفان‌های گردوغبار در هر …