IJSEA Volume 11 Issue 5

Prediction of Copper Mineralization by the Artificial Neural Network (GRNN and BPNN) in Mesgaran Exploration Area, Eastern Iran

Hamed Nazerian, Bahareh Hedayat, Aref Shirazi, Adel Shirazy
10.7753/IJSEA1105.1002
keywords : Artificial Neural Network, ANN, BPNN, Radial Neural Network, South Khorasan, Copper

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Mesgaran exploration area is located in South Khorasan province, 26 km south of Sarbisheh city. The mineral potential of coppersmiths is copper mineralization. According to 75 surface samples taken, the analysis results are examined using the method of radial artificial neural network and error propagation. Also, after training to see the networks, the results can be used for other places. The strength of this study is that it does not require costly analyses to predict copper levels in other parts of the range, and simple analyses can estimate copper levels with an acceptable probability percentage and use the results to advance operations. In this area, the neural method was identified with higher accuracy.
@artical{h1152022ijsea11051002,
Title = "Prediction of Copper Mineralization by the Artificial Neural Network (GRNN and BPNN) in Mesgaran Exploration Area, Eastern Iran ",
Journal ="International Journal of Science and Engineering Applications (IJSEA)",
Volume = "11",
Issue ="5",
Pages ="61 - 65",
Year = "2022",
Authors ="Hamed Nazerian, Bahareh Hedayat, Aref Shirazi, Adel Shirazy"}