Adaptive Neuro-Fuzzy Inference System (Anfis) Based Local Ordinary Kriging Algorithm for Scattered Data Interpolation

Author: Özkan, Coşkun¹

Source: Survey Review, Volume 41, Number 314, October 2009 , pp. 395-407(13)

Publisher: Maney Publishing

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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 show 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.

Keywords: KRIGING; INTERPOLATION; VARIOGRAM MODELLING; ADAPTIVE NEURO-FUZZY INFERENCE

Document Type: Research article

DOI: 10.1179/003962609X451636

Affiliations: 1: Erciyes University, Geodesy and Photogrammetry Engineering Department, 38039, Kayseri, Turkey;, Email: cozkan@erciyes.edu.tr

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