Evaluation of soft computing algorithms for estimation of spatial transmissivity

Tapesh K. Ajmera; Manish Kumar Goyal

doi:10.1504/ijw.2015.068959

Abstract

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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.

Evaluation of soft computing algorithms for estimation of spatial transmissivity

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