Title: Evaluation of soft computing algorithms for estimation of spatial transmissivity

Authors: Tapesh Ajmera; Manish Kumar Goyal

Addresses: Department of Earth and Environmental Sciences, University of Waterloo, Ontario, N2L 3G1, Canada ' Department of Civil Engineering, Indian Institute of Technology, Guwahati-781039, India

Abstract: This paper explored the potential of inverse technique using adaptive network-based fuzzy inference system (ANFIS), self-organised maps (SOMs) and M5P model tree-based regression approach to estimate the spatial transmissivity of aquifer domain. The study is based on coupling of finite element method (FEM)-soft computing (ANFIS, SOMs, M5P) model, which serve as forward (FEM) and inverse (ANN, SOMs, M5P) models. The root mean square error, coefficient of correlation and Nash-Sutcliffe efficiency index are used as comparison criteria for evaluating the models. The results from this study suggest that M5P model tree-based modelling approach is superior in accuracy in comparison to the ANFIS and SOMs model investigated in this study. This study also suggests that M5P model trees, being analogous to piecewise linear functions, have advantages over other techniques as they offer more insight into the developed model and are very efficient in training, and always converge.

Keywords: adaptive neuro-fuzzy inference system; ANFIS; inverse modelling; M5P tree-based regression; self-organised maps; SOMs; soft computing; spatial transmissivity; neural networks; fuzzy logic; aquifers; finite element method; FEM; groundwater modelling; water resource management.

DOI: 10.1504/IJW.2015.068959

International Journal of Water, 2015 Vol.9 No.2, pp.168 - 177

Received: 04 Apr 2013
Accepted: 24 Oct 2013

Published online: 22 Apr 2015 *

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