Adaptive neuro-fuzzy inference system: Estimation of soil aggregates stability

In present study, the capabilities of multiple linear regression (MLR) and adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions (PTFs) for estimating geometric mean diameter (GMD) and mean weight diameter (MWD), from routine soil properties and combination of routine soil properties and fractal dimension of aggregates were evaluated. For this reason 101 samples were collected form the Northwest of Iran and some their properties such as soil texture, pH, cation exchange capacity (CEC), and organic matter (OM), fractal dimension of aggregates between number-diameter (Dn), mass-diameter (Dmt), and bulk density-diameter (Dmy) were determined and used as an input variables for determining of mean weight diameter (MWD) and geometric mean diameter (GMD) by MLR and ANFIS PTFs. Results showed that the application of fractal dimension of aggregates as a predictor in two methods improved the accuracy of PTFs. As well as, results showed that ANFIS have greater potential for determination of the relationships between soil aggregate stability indices and other soil properties in compared with MLR. Therefore using of adaptive neuro-fuzzy inference system (ANFIS) in developing pedotransfer functions is recommended.