Modeling of Soil Cation Exchange Capacity Based on Fuzzy Table Look-up Scheme and Artificial Neural Network Approach

In this study, a new approach is proposed as a modification to a standard fuzzy modeling method based on the table look-up scheme. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, neural network model (feed-forward back propagation network) and fuzzy table look-up scheme were employed to develop a pedotransfer function for predicting soil CEC using easily measurable characteristics of clay and organic carbon. In order to evaluate the models, root mean square error (RMSE) and R 2 were used. The value of RMSE and R 2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for fuzzy table look-up scheme were 0.33 and 0.98 respectively. Results showed that fuzzy table look-up scheme had better performance in predicting and modeling of soil cation exchange capacity than artificial neural network.