Determining the importance of soil properties for clay dispersibility using artificial neural network and daptive neuro-fuzzy inference system

Document Type : Research Paper

Authors

1 Soil Science Department, Vali-e-Asr University

2 Former MSc Student of Soil Science Department, College of Agriculture, Vali-e-Asr University of Rafsanjan, Rafsanjan, Iran

3 Vali-e-Asr University, Rafsanjan, Iran

Abstract

The main purpose of the current research is comparing the results of Artificial Neural Network (ANN) with Adaptive Neuro-Fuzzy Inference System (ANFIS) with regard to determination of the importance of soil properties affecting clay dispersibility. After taking samples from two depths of 0-40 and 40-80 cm, the spontaneous and mechanical dispersions of clay were recorded using both weighing and turbidimetric methods. To determine the degree of importance of soil properties affecting clay dispersibility, first ANNs and ANFIS in MATLAB Software were determined, using all research variables. After determining less effective properties and omitting them, the mentioned networks with the remaining variables including percentage of clay and sand, soil reaction, Electrical Conductivity (EC) and Sodium Adsorption Ratio (SAR) were measured and the degree of importance of each variable in clay dispersibility was determined. Finally, the results of ANNs and ANFIS were compared by calculation of validation parameters. Existence of high correlation between calculated values for weighing and turbidimetric methods showed a linear relationship between the two methods. In general, in both depths and for both weighing and turbidimetric methods, the sensitivity of clay dispersibility to the percentage of the clay, sand and SAR, was higher than any other variable. Although the results obtained from the validation statistics indicate high accuracy of both ANN and ANFIS models, the last model showed relatively better results as compared to ANN model.

Keywords

Main Subjects

References

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Desert
Volume 22, Issue 1
March 2017
Pages 135-143

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