Ata allah Nadiri

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Ata allah Nadiri
Name Ata allah Nadiri
Affiliation عضو هیئت علمی سایر دانشگاههای داخل کشور
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1 Probabilistic human health risk assessment for arsenic, nickel and lead exposures based on two-dimensional Monte Carlo simulation Groundwater for Sustainable Development
2 Subsidence vulnerability indexing using convolutional neural networks based on clustering and regression modeling strategies Groundwater for Sustainable Development
3 Investigating socio-economic and hydrological sustainability of ancient Qanat water systems in arid regions of central Iran Groundwater for Sustainable Development
4 Removal of arsenic with functionalized multiwalled carbon nanotubes (MWCNTs-COOH) using the magnetic method (Fe3O4) from aqueous solutions RSC Advances
5 Quantifying the groundwater total contamination risk using an inclusive multi-level modelling strategy Journal of Environmental Management
6 Developing a Data-Fused Water Quality Index Based on Artificial Intelligence Models to Mitigate Conflicts between GQI and GWQI Water
7 Introducing dynamic land subsidence index based on the ALPRIFT framework using artificial intelligence techniques Earth Science Informatics
8 Investigating meteorological/groundwater droughts by copula to study anthropogenic impacts Scientific Reports
9 Formulating GA-SOM as a Multivariate Clustering Tool for Managing Heterogeneity of Aquifers in Prediction of Groundwater Level Fluctuation by SVM Model Iranian Journal of Science and Technology-Transactions of Civil Engineering
10 A study of uncertainties in groundwater vulnerability modelling using Bayesian model averaging (BMA) Journal of Environmental Management
11 Formulating Convolutional Neural Network for mapping total aquifer vulnerability to pollution ENVIRONMENTAL POLLUTION
12 An investigation into time-variant subsidence potentials using inclusive multiple modelling strategies Journal of Environmental Management
13 Mapping Risk to Land Subsidence: Developing a Two-Level Modeling Strategy by Combining Multi-Criteria Decision-Making and Artificial Intelligence Techniques Water
14 Next Stages in Aquifer Vulnerability Studies by Integrating Risk Indexing with Understanding Uncertainties by using Generalised Likelihood Uncertainty Estimation Exposure and Health
15 An investigation into uncertainties within Human Health Risk Assessment to gain an insight into plans to mitigate impacts of arsenic contamination JOURNAL OF CLEANER PRODUCTION
16 An investigation to human health risks from multiple contaminants and multiple origins by introducing‘Total Information Management’ ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
17 Transforming subsidence vulnerability indexing based on ALPRIFT into risk indexing using a new fuzzy-catastrophe scheme ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
18 Vulnerability Indexing to Saltwater Intrusion from Models at Two Levels using Artificial Intelligence Multiple Model (AIMM) Journal of Environmental Management
19 Formulating a strategy to combine artificial intelligence models using Bayesian model averaging to study a distressed aquifer with sparse data availability JOURNAL OF HYDROLOGY
20 Groundwater Remediation through Pump-Treat-Inject Technology Using Optimum Control by Artificial Intelligence (OCAI) WATER RESOURCES MANAGEMENT
21 Mapping specific vulnerability of multiple confined and unconfined quifers by using artificial intelligence to learn from multiple DRASTIC frameworks Journal of Environmental Management
22 Mapping groundwater potential field using catastrophe fuzzy membership functions and Jenks optimization method: a case study of Maragheh-Bonab plain, Iran Environmental Earth Sciences
23 Localization of Groundwater Vulnerability Assessment Using Catastrophe Theory WATER RESOURCES MANAGEMENT
24 Introducing a risk aggregation rationale for mapping risks to aquifers from point- and diffuse-sources–proof-of-concept using contamination data from industrial lagoons ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
25 Introducing the risk aggregation problem to aquifers exposed to impacts of anthropogenic and geogenic origins on a modular basis using ‘risk cells’ Journal of Environmental Management
26 Groundwater vulnerability indices conditioned by Supervised Intelligence Committee Machine (SICM) SCIENCE OF THE TOTAL ENVIRONMENT