[PDF][PDF] Application of remote sensing in earth sciences–A review

A Shirazy, A Shirazi, H Nazerian - International Journal of Science and …, 2021 - ijsea.com
The application of remote sensing sciences in the field of geology is very diverse and wide.
One of its most important applications in earth sciences is geological map**. Mineral …

Fusion of remote sensing, magnetometric, and geological data to identify polymetallic mineral potential zones in Chakchak Region, Yazd, Iran

AA Aali, A Shirazy, A Shirazi, AB Pour, A Hezarkhani… - Remote Sensing, 2022 - mdpi.com
Exploration geologists are urged to develop new, robust, and low-cost approaches to
identify high potential zones related to underground/unexplored mineral deposits because …

Hybrid fuzzy-analytic hierarchy process (AHP) model for porphyry copper prospecting in simorgh area, eastern lut block of Iran

V Khosravi, A Shirazi, A Shirazy, A Hezarkhani… - Mining, 2021 - mdpi.com
The eastern Lut block of Iran has a high potential for porphyry copper mineralization due to
the subduction tectonic regime. It is located in an inaccessible region and has harsh arid …

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 …

A Shirazy, A Hezarkhani, T Timkin, A Shirazi - Minerals, 2021 - mdpi.com
The study area is located near Toot village in the Yazd province of Iran, which is considered
in terms of its iron mineralization potential. In this area, due to radioactivity, radiometric …

[HTML][HTML] Geochemical behavior investigation based on k-means and artificial neural network prediction for titanium and zinc, Kivi region, Iran

S Adel, Z Mansour, H Ardeshir - Известия Томского …, 2021 - cyberleninka.ru
The relevance. These are the first studies in the Kivi region. Due to the presence of titanium
and zinc in the area, these studies are necessary. Artificial Neural Network and K-means …

K-means clustering and general regression neural network methods for copper mineralization probability in Chahar-Farsakh, Iran

A Shirazy, A Hezarkhani, A Shirazi… - Türkiye Jeoloji …, 2022 - dergipark.org.tr
Due to the efficiency of data mining science for analyzing and reviewing extensive data,
especially geochemical data, essential methods and techniques such as the hierarchical …

Geochemical Modeling of Copper Mineralization Using Geostatistical and Machine Learning Algorithms in the Sahlabad Area, Iran

A Shirazi, A Hezarkhani, A Shirazy, AB Pour - Minerals, 2023 - mdpi.com
Analyzing geochemical data from stream sediment samples is one of the most proactive
tools in the geochemical modeling of ore mineralization and mineral exploration. The main …

[PDF][PDF] Determination of Archie's Tortuosity Factor from Stoneley Waves in Carbonate Reservoirs

K Khayer, A Shirazy, A Shirazi, A Ansari… - International Journal of …, 2021 - ijsea.com
One of the fundamental equations in calculate the saturation of fluid in hydrocarbon
reservoirs is the Archie's equation. In addition to the parameters measured by well logging …

[PDF][PDF] 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 …

H Nazerian, A Shirazy, A Shirazi… - International Journal of …, 2022 - ijsea.com
Artificial neural network (ANN) is one of the practical methods for prediction in various
sciences. In this study, which was carried out on Glass and Crystal Factory in Isfahan, the …

Geochemical and hydrothermal alteration patterns of the abrisham-rud porphyry copper district, semnan province, Iran

T Timkin, M Abedini, M Ziaii, MR Ghasemi - Minerals, 2022 - mdpi.com
In this study, the zonality method has been used to separate geochemical anomalies and to
calculate erosional levels in the regional scale for porphyry-Cu deposit, Abrisham-Rud …