ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM (ANFIS) BASED LOCAL ORDINARY KRIGING ALGORITHM FOR SCATTERED DATA INTERPOLATION


Ozkan C.

SURVEY REVIEW, vol.41, no.314, pp.395-407, 2009 (Journal Indexed in SCI) identifier identifier

  • Publication Type: Article / Article
  • Volume: 41 Issue: 314
  • Publication Date: 2009
  • Doi Number: 10.1179/003962609x451636
  • Title of Journal : SURVEY REVIEW
  • Page Numbers: pp.395-407

Abstract

A new approach to the Ordinary Kriging interpolation method based on the combination of local interpolation and variogram modelling with Adaptive Neuro-Fuzzy Inference System (ANFIS) is proposed for scattered data interpolation. In this method, the experimental variogram is modelled by ANFIS and this model is used to interpolate the unknown values of specific points in a new local manner. In this local way, all the unknown points are grouped based on each reference point. The study data obtained from mathematical functions are used. The tests shou, that the proposed method provides better performances for all data sets in comparison to the well known and highly approved interpolation methods; Ordinary Kriging, Triangle Based Cubic and Radial Basis Function-Multiquadric. Moreover, by the proposed method the computational complexity impressively decreases compared to the global ordinary Kriging.