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Bahri, Esmaeil, Alimoradi, Andisheh, Yousefi, Mahyar. (1402). Investigating the performance of continuous weighting functions in the integration of exploration data for mineral potential modeling using artificial neural networks, geometric average and fuzzy gamma operators. , (), -. doi: 10.22059/ijmge.2023.361593.595080
Esmaeil Bahri; Andisheh Alimoradi; Mahyar Yousefi. "Investigating the performance of continuous weighting functions in the integration of exploration data for mineral potential modeling using artificial neural networks, geometric average and fuzzy gamma operators". , , , 1402, -. doi: 10.22059/ijmge.2023.361593.595080
Bahri, Esmaeil, Alimoradi, Andisheh, Yousefi, Mahyar. (1402). 'Investigating the performance of continuous weighting functions in the integration of exploration data for mineral potential modeling using artificial neural networks, geometric average and fuzzy gamma operators', , (), pp. -. doi: 10.22059/ijmge.2023.361593.595080
Bahri, Esmaeil, Alimoradi, Andisheh, Yousefi, Mahyar. Investigating the performance of continuous weighting functions in the integration of exploration data for mineral potential modeling using artificial neural networks, geometric average and fuzzy gamma operators. , 1402; (): -. doi: 10.22059/ijmge.2023.361593.595080

Investigating the performance of continuous weighting functions in the integration of exploration data for mineral potential modeling using artificial neural networks, geometric average and fuzzy gamma operators

International Journal of Mining and Geo-Engineering
مقالات آماده انتشار، اصلاح شده برای چاپ، انتشار آنلاین از تاریخ 23 مرداد 1402
نوع مقاله: Research Paper
شناسه دیجیتال (DOI): 10.22059/ijmge.2023.361593.595080
نویسندگان
Esmaeil Bahri* 1؛ Andisheh Alimoradi1؛ Mahyar Yousefi2
1Department of Mining and Petroleum Engineering, Faculty of Engineering, Imam Khomeini International University
2Department of Mining Engineering, Faculty of Engineering, Malayer University
چکیده
In mineral exploration programs, reducing uncertainty and increasing the exploration success have always been of challenging issues. To modulate the above-mentioned uncertainty and to increase the exploration success, integration and prospectivity analysis techniques are used for mineral exploration targeting. This paper aims to model mineral potential of porphyry copper deposits in Jiroft region, Kerman province. To achieve this goal and to overcome the aforementioned issues resulting from the operation of complex ore-forming geological processes, continuous weighting methods through logistic functions were used while training points and analyst’s opinion were not contributed in the weighting procedure. Then, to generate exploration targets the weighted layers were combined with three different integration methods namely, artificial neural network, geometric average and fuzzy gamma operators. Comparison of the model obtained from the application of artificial neural network with those models obtained by the geometric average and the fuzzy gamma operators by using prediction rate-area plots, indicated that all the models have good overall performance and acceptable prediction rate. However, the performance of the artificial neural network model is slightly less than that of other two models. Thus, the targets generated using geometric average and fuzzy gamma operators are more reliable for planning further exploration programs.
کلیدواژه‌ها
Artificial neural network؛ Exploration targets؛ Fuzzy gamma؛ Geometric average؛ Porphyry copper deposits
آمار
تعداد مشاهده مقاله: 53


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