Prediction of CEC using fractal parameters by artificial neural networks

• Autorzy: Bayat H. , Davatgar N. , Jalali M.
• Języki publikacji: EN

Abstrakty

EN

The prediction of cation exchange capacity from readily available soil properties remains a challenge. In this study, firstly, we extended the entire particle size distribution curve from limited soil texture data and, at the second step, calculated the fractal parameters from the particle size distribution curve. Three pedotransfer functions were developed based on soil properties, parameters of particle size distribution curve model and fractal parameters of particle size distribution curve fractal model using the artificial neural networks technique. 1 662 soil samples were collected and separated into eight groups. Particle size distribution curve model parameters were estimated from limited soil texture data by the Skaggs method and fractal parameters were calculated by Bird model. Using particle size distribution curve model parameters and fractal parameters in the pedotransfer functions resulted in improvements of cation exchange capacity predictions. The pedotransfer functions that used fractal parameters as predictors performed better than the those which used particle size distribution curve model parameters. This can be related to the non-linear relationship between cation exchange capacity and fractal parameters. Partitioning the soil samples significantly increased the accuracy and reliability of the pedotransfer functions. Substantial improvement was achieved by utilising fractal parameters in the clusters.

Słowa kluczowe

EN

cation exchange capacity; prediction; fractal structure; fractal theory; particle size distribution; artificial neural network; pedotransfer function

• Wydawca: -
• Czasopismo: International Agrophysics
• Rocznik: 2014
• Tom: 28
• Numer: 2
• Opis fizyczny: p.143-152,fig.,ref.

Twórcy

autor

Bayat H.

• Department of Soil Science, Bu Ali Sina University, Hamadan, Iran

autor

Davatgar N.

• Department of Soil Science, Rice Research Institute of Iran, Rasht, Iran

autor

Jalali M.

• Department of Soil Science, Bu Ali Sina University, Hamadan, Iran

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