Journal of Range and Watershed Managment

Application of CANFIS Model in Prediction of Soil Cation Exchange Capacity in Some Arid and Semi-Arid Regions of Iran

Document Type : Research Paper

Authors

Fereydoon Sarmadian 1
Ali Keshavarzi 2

1 Professor, Department of Soil Science, Faculty of Agricultural Engineering & Technology, University of Tehran. I.R. IRAN.

2 Assistant Professor, Department of Soil Science, Faculty of Agricultural Engineering & Technology, University of Tehran. I.R.IRAN.

https://doi.org/10.22059/jrwm.2016.61691
Abstract
Data mining enables generalization of data of soil to remote areas and which is able to up/down scale of data in wide ranges of level that facilitate the decision-making process of executives. Cation Exchange Capacity (CEC) is one of the most important parameters in soil database and shows the ability of a soil to retention of minerals and pollutants. Due to low organic matter and specific mineralogy of soils in arid and semi-arid regions, measurement of CEC is time consuming and expensive. The objective of this study was to evaluate Coactive Neuro-Fuzzy Inference System (CANFIS) in prediction of CEC in soils of arid and semi-arid regions. A total of 85 soil samples from target area were selected among 440 soil sample database (available reference database) with a ratio of 1:5. Correlation test was conducted to assess the co-linearity of independent variables. Forward regression model was used to determine the most important and influential input parameters on the output results. The results indicated the reliability and high performance of the CANFIS approach in estimation of CEC using easily measurable characteristics, organic material, and satellite images.

Keywords

soil database
Data Mining
CEC
easily measurable characteristics
CANFIS
Journal of Range and Watershed Managment
Volume 69, Issue 2
Summer 2016
Pages 397-410

  • Receive Date 22 January 2014
  • Revise Date 03 August 2016
  • Accept Date 09 February 2015
  • Publish Date 21 June 2016

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