Search Results - "BARZEGAR, Rahim"

Short-term water quality variable prediction using a hybrid CNN–LSTM deep learning model by Barzegar, Rahim, Aalami, Mohammad Taghi, Adamowski, Jan

“…Water quality monitoring is an important component of water resources management. In order to predict two water quality variables, namely dissolved oxygen (DO;…”
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Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models by Barzegar, Rahim, Fijani, Elham, Asghari Moghaddam, Asghar, Tziritis, Evangelos

“…Accurate prediction of groundwater level (GWL) fluctuations can play an important role in water resources management. The aims of the research are to evaluate…”
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Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River, Iran by Barzegar, Rahim, Adamowski, Jan, Moghaddam, Asghar Asghari

“…The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water…”
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Using bootstrap ELM and LSSVM models to estimate river ice thickness in the Mackenzie River Basin in the Northwest Territories, Canada by Barzegar, Rahim, Ghasri, Mahsa, Qi, Zhiming, Quilty, John, Adamowski, Jan

“…•Bootstrap ELM and LSSVM used for ice river thickness estimation.•Easy to measure meteorological variables used as predictors.•Bootstrap ELM model outperformed…”
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An ensemble tree-based machine learning model for predicting the uniaxial compressive strength of travertine rocks by Barzegar, Rahim, Sattarpour, Masoud, Deo, Ravinesh, Fijani, Elham, Adamowski, Jan

“…Estimating the uniaxial compressive strength (UCS) of travertine rocks with an indirect modeling approach and machine learning algorithms is useful as models…”
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A supervised committee machine artificial intelligent for improving DRASTIC method to assess groundwater contamination risk: a case study from Tabriz plain aquifer, Iran by Barzegar, Rahim, Moghaddam, Asghar Asghari, Baghban, Hamed

“…Vulnerability maps are designed to show areas of greatest potential for groundwater contamination on the basis of hydrogeological conditions and human impacts…”
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Developing a SINTACS-based method to map groundwater multi-pollutant vulnerability using evolutionary algorithms by Jahromi, Maryam Naghdizadegan, Gomeh, Zinat, Busico, Gianluigi, Barzegar, Rahim, Samany, Najmeh Neysani, Aalami, Mohammad Taghi, Tedesco, Dario, Mastrocicco, Micol, Kazakis, Nerantzis

“…In this study, the modified SINTACS method, a rating-based groundwater vulnerability approach, was applied to data from the Campanian Plain, southern Italy, to…”
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Developing a Data-Fused Water Quality Index Based on Artificial Intelligence Models to Mitigate Conflicts between GQI and GWQI by Nadiri, Ata Allah, Barzegar, Rahim, Sadeghfam, Sina, Rostami, Ali Asghar

“…The study of groundwater quality is typically conducted using water quality indices such as the Groundwater Quality Index (GQI) or the GroundWater Quality…”
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Mapping Risk to Land Subsidence: Developing a Two-Level Modeling Strategy by Combining Multi-Criteria Decision-Making and Artificial Intelligence Techniques by Nadiri, Ata Allah, Moazamnia, Marjan, Sadeghfam, Sina, Barzegar, Rahim

“…Groundwater over-abstraction may cause land subsidence (LS), and the LS mapping suffers the subjectivity associated with expert judgment. The paper seeks to…”
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Establishing a Data Fusion Water Resources Risk Map Based on Aggregating Drinking Water Quality and Human Health Risk Indices by Nadiri, Ata Allah, Sedghi, Zahra, Barzegar, Rahim, Nikoo, Mohammad Reza

“…The Drinking Water Quality Index (DWQI) and the Human Health Risk Index (HHRI) are two of the most promising tools for assessing the health impact of water…”
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Multi-step ahead soil temperature forecasting at different depths based on meteorological data: Integrating resampling algorithms and machine learning models by KHOSRAVI, Khabat, GOLKARIAN, Ali, BARZEGAR, Rahim, AALAMI, Mohammad T., HEDDAM, Salim, OMIDVAR, Ebrahim, KEESSTRA, Saskia D., LÓPEZ-VICENTE, Manuel

“…Direct soil temperature (ST) measurement is time-consuming and costly; thus, the use of simple and cost-effective machine learning (ML) tools is helpful. In…”
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Breast Tuberculosis in Iran: A Comprehensive Review by Babamahmoodi, Farhang, Babamahmoodi, Abdolreza, Barzegar, Rahim, Sadr, Makan, Rezaei, Mitra, Marjani, Majid

“…Tuberculosis (TB) remains a significant global health concern and kills millions of people every year. While TB can affect any organ in the body, breast TB is…”
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Effects of biofertilizer on the production of bell pepper (Capsicum annuum L.) in greenhouse by Nejati Sini, Hossein, Barzegar, Rahim, Soodaee Mashaee, Saheb, Ghasemi Ghahsare, Masood, Mousavi-Fard, Sadegh, Mozafarian, Maryam

“…Biological fertilizers are useful sources of plant nutrients that enhance crop growth and quality, produce plant hormones, and contribute to sustainable crop…”
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Comparing the Soil Conservation Service model with new machine learning algorithms for predicting cumulative infiltration in semi-arid regions by KHOSRAVI, Khabat, NGO, Phuong T.T., BARZEGAR, Rahim, QUILTY, John, AALAMI, Mohammad T., BUI, Dieu T.

“…Water infiltration into soil is an important process in hydrologic cycle; however, its measurement is difficult, time-consuming and costly. Empirical and…”
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Coupling a hybrid CNN-LSTM deep learning model with a Boundary Corrected Maximal Overlap Discrete Wavelet Transform for multiscale Lake water level forecasting by Barzegar, Rahim, Aalami, Mohammad Taghi, Adamowski, Jan

“…•The BC-MODWT preprocessing method coupled with CNN-LSTM DL and ML models (i.e. SVR and RF) was developed for multistep WL forecasting.•The DL model…”
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Using ensembles of adaptive neuro-fuzzy inference system and optimization algorithms to predict reference evapotranspiration in subtropical climatic zones by Roy, Dilip Kumar, Barzegar, Rahim, Quilty, John, Adamowski, Jan

“…•Hybridized ANFIS models are proposed for predicting ET0.•Performances of the hybrid models are compared with the classic ANFIS model.•Entropy, variation…”
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Design and implementation of a hybrid model based on two-layer decomposition method coupled with extreme learning machines to support real-time environmental monitoring of water quality parameters by Fijani, Elham, Barzegar, Rahim, Deo, Ravinesh, Tziritis, Evangelos, Skordas, Konstantinos

“…Accurate prediction of water quality parameters plays a crucial and decisive role in environmental monitoring, ecological systems sustainability, human health,…”
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Mapping groundwater contamination risk of multiple aquifers using multi-model ensemble of machine learning algorithms by Barzegar, Rahim, Moghaddam, Asghar Asghari, Deo, Ravinesh, Fijani, Elham, Tziritis, Evangelos

“…•A DRASTIC vulnerability map, with an r of 0.64, was developed for a multiple aquifer system (e.g. unconfined, semi-confined and confined)•DRASTIC method was…”
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Improving GALDIT-based groundwater vulnerability predictive mapping using coupled resampling algorithms and machine learning models by Barzegar, Rahim, Razzagh, Siamak, Quilty, John, Adamowski, Jan, Kheyrollah Pour, Homa, Booij, Martijn J.

“…•Machine learning (ML) based GALDIT models were proposed to evaluate groundwater vulnerability.•Boosting and tree-based models are capable of reducing the…”
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Withdrawn: Similar Isotopic Biases of Plant Stem Bulk Water From Different Water Sources by Cryogenic Vacuum Distillation Demonstrated Through Rehydration Experiments by Zhao, Pei, Sprenger, Matthias, Barzegar, Rahim, Tang, Xiangyu, Adamowski, Jan

“…Zhao, P., Sprenger, M., Barzegar, R., Tang, X., & Adamowski, J. (2022). Similar isotopic biases of plant stem bulk water from different water sources by…”
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