Tutmez, Bulent2024-08-042024-08-0420100941-06431433-3058https://doi.org/10.1007/s00521-009-0326-3https://hdl.handle.net/11616/95043Aquifer 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.eninfo:eu-repo/semantics/closedAccessPorosityPoint semimadogramNeuro-fuzzy inferenceRadial basis functionArticle19349950510.1007/s00521-009-0326-32-s2.0-77952879990Q1WOS:000275755000016Q4