期刊
NEURAL COMPUTING & APPLICATIONS
卷 19, 期 3, 页码 499-505出版社
SPRINGER LONDON LTD
DOI: 10.1007/s00521-009-0326-3
关键词
Porosity; Point semimadogram; Neuro-fuzzy inference; Radial basis function
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.
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