Assessment of porosity using spatial correlation-based radial basis function and neuro-fuzzy inference system

Tutmez B.

NEURAL COMPUTING & APPLICATIONS, cilt.19, sa.3, ss.499-505, 2010 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 19 Sayı: 3
  • Basım Tarihi: 2010
  • Doi Numarası: 10.1007/s00521-009-0326-3
  • Dergi Adı: NEURAL COMPUTING & APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.499-505
  • İnönü Üniversitesi Adresli: Evet

Özet

Aquifer porosity indicates the storage groundwater capacity and groundwater quality. It may be measured via different techniques. This paper presents a novel spatial methodology based on radial basis function (RBF) and neuro-fuzzy inference system for modelling the porosity. Use of the point cumulative semimadogram in RBF as a spatial measure is a novel contribution. In addition, the methodology examines the use of a neural network-based fuzzy inference system for porosity estimation. Performance comparisons with conventional methods show that the proposed spatial model has high modelling and generalization capability.