Algorithms for clustering data
Algorithms for clustering data
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
Neuro-fuzzy and soft computing: a computational approach to learning and machine intelligence
International Journal of Human-Computer Studies
Modelling electrical conductivity of groundwater using an adaptive neuro-fuzzy inference system
Computers & Geosciences
On cluster validity for the fuzzy c-means model
IEEE Transactions on Fuzzy Systems
An uncertainty oriented fuzzy methodology for grade estimation
Computers & Geosciences
Expert Systems with Applications: An International Journal
Spatial dependence-based fuzzy regression clustering
Applied Soft Computing
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This paper addresses a spatial estimation model which uses fuzzy clustering algorithm and assesses the aquifer porosity based on point cumulative semimadogram (PCSM) measure. In order to obtain the estimated porosity values, the model employs standard regional dependence function (SRDF) which provides weights for different regional locations depending on the distances from the reference site. The proposed methodology has three stages: (1) structure identification; (2) spatial dependence measure; and (3) interpolation. The model has been tested using a real data set which was taken from an aquifer in Turkey. The performance evaluations indicate that the new methodology can be applied in geological based domains.