Use of hybrid intelligent computing in mineral resources evaluation

Tutmez B.

APPLIED SOFT COMPUTING, cilt.9, sa.3, ss.1023-1028, 2009 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 9 Sayı: 3
  • Basım Tarihi: 2009
  • Doi Numarası: 10.1016/j.asoc.2009.02.001
  • Dergi Adı: APPLIED SOFT COMPUTING
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.1023-1028
  • İnönü Üniversitesi Adresli: Evet

Özet

Mineral resources are a formal quantification of naturally occurring materials. Estimation of resource parameters such as grade and thickness may be carried out using different methodologies. In this paper, a soft methodology, which is artificial neural network (ANN) based fuzzy modelling is presented for grade estimation and its stages are demonstrated. The neuro-fuzzy method uses preliminary clustering and finally estimates the ore grades based on radial basis neural network and interpolation. Two case studies designed for both simulated and real data sets indicate that the approach is relatively accurate and flexible. In addition, the method is suitable for modelling via limited number of data. The results and performance comparisons with conventional methods show that the computing method is efficient. (C) 2009 Elsevier B.V. All rights reserved.