Investigation of the Usability of Soft Computing Methods to Determine the Quality Distribution in Metallic Mine

ÖZDEMİR A. C.

JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING, cilt.37, sa.5-6, ss.493-502, 2021 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 37 Sayı: 5-6
  • Basım Tarihi: 2021
  • Dergi Adı: JOURNAL OF MULTIPLE-VALUED LOGIC AND SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, zbMATH
  • Sayfa Sayıları: ss.493-502
  • Anahtar Kelimeler: Metallic mine, quality distribution, soft computing methods, tenor, ARTIFICIAL NEURAL-NETWORK, PREDICTION, DEPOSITS, DESIGN
  • Çukurova Üniversitesi Adresli: Evet

Özet

For successful mining, the activities carried out must provide maximum profitability and be sustainable. These conditions will be ensured by performing detailed mine planning studies and applying these plans correctly in mines. Given the regional variability of mines, the quality distribution must be determined. At this stage, the modeling or estimation methods in the literature that will be used are a matter of debate. This study aimed to investigate the usability of artificial neural networks (ANNs), which are one of the soft computing methods, for determining quality distribution by estimating to the tenor of metallic mine fields. In this study, a sample application field was selected. The tenor values of this field were estimated with 71% correlation coefficient, and quality distribution was determined. The results showed that the ANN method can be an alternative to widely used modeling and estimation methods.