Comparative Evaluation of Prediction Model between Inference Fuzzy System and Universal Kriging for Spatial Data

Ghanim Mahmood Dhaher ()

Technium, 2022, vol. 4, issue 1, 115-125

Abstract: This paper dealt with one of the spatial interpolation methods in the geostatistics field. The purpose of this research is to get the parameters of unbiased estimators based on regionalized random variables in spatial statistics. In this paper, we used universal kriging with the fuzzy inference system by the Mamdani technique. the objective of this work is to estimate the parameters of covariance functions relying on spatial real for the depth of groundwater in Mosul city, Iraq. The data adopted contains (100) real data with locations representing the depth. From the results we show the best model with the constructs of weights, we illustrate the performance of universal kriging is the best when corresponding with the fuzzy system. In conclusion, the improvement of any method of spatial interpolation or fuzzy system does not depend on more statistical structures but depends on the efficiency of the method which satisfies the conditions of weights and minimum variance errors. All programming is applied by Matlab language.

Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://techniumscience.com/index.php/technium/article/view/7824/2839 (application/pdf)
https://techniumscience.com/index.php/technium/article/view/7824 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:tec:techni:v:4:y:2022:i:1:p:115-125

DOI: 10.47577/technium.v4i10.7824

Access Statistics for this article

Technium is currently edited by Scurtu Ionut Cristian

More articles in Technium from Technium Science
Bibliographic data for series maintained by Ana Maria Golita ().