Table of Contents
ISRN Soil Science
Volume 2013 (2013), Article ID 308159, 8 pages
http://dx.doi.org/10.1155/2013/308159
Research Article

Predicting Saturated Hydraulic Conductivity by Artificial Intelligence and Regression Models

1Department of Soil Science, Faculty of Agrriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran
2Department of Soil Science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran
3School of Engineering, University of Guelph, Guelph, ON, Canada

Received 7 April 2013; Accepted 12 May 2013

Academic Editors: G. Benckiser, D. Hui, H. K. Pant, and D. Zhou

Copyright © 2013 R. Rezaei Arshad et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

R. Rezaei Arshad, Gh. Sayyad, M. Mosaddeghi, and B. Gharabaghi, “Predicting Saturated Hydraulic Conductivity by Artificial Intelligence and Regression Models,” ISRN Soil Science, vol. 2013, Article ID 308159, 8 pages, 2013. doi:10.1155/2013/308159