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Neuro-Fuzzy Approach for Predicting the Infiltration of Soil

  • Saurabh GautamEmail author
  • Parveen Sihag
  • N. K. Tiwari
  • Subodh Ranjan
Conference paper
Part of the Lecture Notes in Civil Engineering book series (LNCE, volume 31)

Abstract

This paper aims to develop an adaptive neuro-fuzzy inference system (ANFIS) approach based model for predicting the infiltration of sandy loam soil. To achieve the objective, cumulative infiltration was observed from prepared soil samples at different moisture contents and different densities with the help of minidisk infiltrometer. Input dataset consists of time, the percentage of sand and clay, moisture content, and bulk density, whereas cumulative infiltration was taken as a target. Different membership functions, i.e., triangular, trapezoidal, Gaussian, and generalized bell-shaped, were implemented in ANFIS-based models. Using statistical performance indices, coefficient of correlation (C.C), root mean square (RMSE), and Nash–Sutcliffe efficiency coefficient (NS) were selected to compare the performance of ANFIS-based models and Kostiakov model. Obtained results suggest that Gaussian-based membership function based on ANFIS model had higher prediction performance than other discussed models.

Keywords

Adaptive neuro-fuzzy inference system Kostiakov model Cumulative infiltration Coefficient of correlation Nash–Sutcliffe efficiency coefficient 

References

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Saurabh Gautam
    • 1
    Email author
  • Parveen Sihag
    • 1
  • N. K. Tiwari
    • 1
  • Subodh Ranjan
    • 1
  1. 1.National Institute of Technology KurukshetraKurukshetraIndia

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