COMPARISON OF ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION METHODS IN PREDICTION OF SOIL CATION EXCHANGE CAPACITY (CASE STUDY: ZIARAN REGION)

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KESHAVARZI A.; SARMADIAN F.

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Journal: Desert Year:2010 | Volume:15 | Issue:2 Page(s): 167-174

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Title

COMPARISON OF ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION METHODS IN PREDICTION OF SOIL CATION EXCHANGE CAPACITY (CASE STUDY: ZIARAN REGION)

Author(s)

KESHAVARZI A. | SARMADIAN F. | Issue Writer Certificate

Keywords

EASILY MEASURABLE CHARACTERISTICS

FEED-FORWARD BACK PROPAGATION

HIDDEN LAYER

PEDOTRANSFER FUNCTIONS

CEC

ZIARAN

Abstract

Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study ofenvironmental reaserches as the spatial and temporal variability of this property have been led to development ofindirect methods in estimation of this soil characteristic. PEDOTRANSFER FUNCTIONS (PTFs) provide an alternative byestimating soil parameters from more readily available soil data. 70 soil samples were collected from differenthorizons of 15 soil profiles located in the ZIARAN region, Qazvin province, Iran. Then, multivariate regression andneural network model (feed-forward back propagation network) were employed to develop a pedotransfer functionfor predicting soil parameter using EASILY MEASURABLE CHARACTERISTICS of clay and organic carbon. The performance of the multivariate regression and neural network model was evaluated using a test data set. In order to evaluate themodels, root mean square error (RMSE) was used. The value of RMSE and R2 derived by ANN model for CEC were0. 47 and 0.94 respectively, while these parameters for multivariate regression model were 0.65 and 0.88 respectively.Results showed that artificial neural network with seven neurons in HIDDEN LAYER had better performance in predictingsoil cation exchange capacity than multivariate regression.

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APA: Copy

KESHAVARZI, A., & SARMADIAN, F.. (2010). COMPARISON OF ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION METHODS IN PREDICTION OF SOIL CATION EXCHANGE CAPACITY (CASE STUDY: ZIARAN REGION). DESERT (BIABAN), 15(2), 167-174. SID. https://sid.ir/paper/569717/en

Vancouver: Copy

KESHAVARZI A., SARMADIAN F.. COMPARISON OF ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION METHODS IN PREDICTION OF SOIL CATION EXCHANGE CAPACITY (CASE STUDY: ZIARAN REGION). DESERT (BIABAN)[Internet]. 2010;15(2):167-174. Available from: https://sid.ir/paper/569717/en

IEEE: Copy

A. KESHAVARZI, and F. SARMADIAN, “COMPARISON OF ARTIFICIAL NEURAL NETWORK AND MULTIVARIATE REGRESSION METHODS IN PREDICTION OF SOIL CATION EXCHANGE CAPACITY (CASE STUDY: ZIARAN REGION),” DESERT (BIABAN), vol. 15, no. 2, pp. 167–174, 2010, [Online]. Available: https://sid.ir/paper/569717/en

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