has been cited by the following article(s):
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[1]
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Design of an artificial neural network (bpnn) to predict the content of silicon oxide (SiO2) based on the values of the rock main oxides: Glass factory feed case …
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International Journal of …,
2022 |
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[2]
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A Review of Mineralization of Rare Earth Elements in Iran
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International Journal of …,
2022 |
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[3]
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Feasibility of simultaneous application of fuzzy neural network and TOPSIS integrated method in potential mapping of lead and zinc mineralization in Isfahan …
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Open Journal of …,
2022 |
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[4]
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Permeability Estimation from Stoneley Waves in Carbonate Reservoirs
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Türkiye Jeoloji …,
2022 |
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[5]
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The Strategies of Chromite Terrace in Sukinda Valley, India: An Appraisal
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Journal of Scientific …,
2022 |
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[6]
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Geochemical relations among elements in stream sediment samples from Siojan Prospecting Area, Iran using geostatistical methods
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Ruhuna Journal of …,
2022 |
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[7]
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Assessment of the Influence of Sulfuric Acid/Hydrogen Peroxide Mixture on Organic Sulfur Reduction of High Sulfur Coals and Their Chemical Composition
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Open Journal of …,
2022 |
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[8]
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Geophysical Study to Identify Iron Mineralization Anomalies Using Terrestrial Magnetometry in the Chak-Chak Exploration Area, Iran
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Türkiye Jeoloji …,
2022 |
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[9]
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Türkiye Jeoloji Bülteni
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Geological Bulletin of …,
2022 |
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[10]
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Geochemical and Behavioral Modeling of Phosphorus and Sulfur as Deleterious Elements of Iron Ore to Be Used in Geometallurgical Studies, Sheytoor Iron …
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Open Journal of …,
2021 |
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[11]
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Investigation of Geochemical Sections in Exploratory Boreholes of Mesgaran Copper Deposit in Iran
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International Journal for …,
2021 |
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[12]
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Application of Remote Sensing in Earth Sciences–A Review
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2021 |
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[13]
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Determination of Archie's Tortuosity Factor from Stoneley Waves in Carbonate Reservoirs
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2021 |
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[14]
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Geophysical study: Estimation of deposit depth using gravimetric data and Euler method (Jalalabad iron mine, kerman province of IRAN)
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2021 |
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[15]
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Investigation of magneto-/radio-metric behavior in order to identify an estimator model using K-means clustering and Artificial Neural Network (ANN)(Iron Ore …
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Minerals,
2021 |
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[16]
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Prediction of Copper Mineralization by the Artificial Neural Network (GRNN & BPNN) in Mesgaran Exploration Area, Eastern Iran
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[1]
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From waste to wealth: Unlocking the value of copper anode slimes through systematic characterization and pretreatment
Minerals Engineering,
2023
DOI:10.1016/j.mineng.2023.108141
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[2]
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From waste to wealth: Unlocking the value of copper anode slimes through systematic characterization and pretreatment
Minerals Engineering,
2023
DOI:10.1016/j.mineng.2023.108141
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[3]
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Geophysical Studies to Identify Iron Mineralization Anomalies Using Terrestrial Magnetometry in The ChakChak Area
Türkiye Jeoloji Bülteni / Geological Bulletin of Turkey,
2022
DOI:10.25288/tjb.1035354
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[4]
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Permeability Estimation From stoneley Waves in Carbonate Reservoirs
Türkiye Jeoloji Bülteni / Geological Bulletin of Turkey,
2021
DOI:10.25288/tjb.974505
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[5]
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Investigation of Magneto-/Radio-Metric Behavior in Order to Identify an Estimator Model Using K-Means Clustering and Artificial Neural Network (ANN) (Iron Ore Deposit, Yazd, IRAN)
Minerals,
2021
DOI:10.3390/min11121304
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