S. Ayoubi

Spatial prediction of USDA‐ great soil groups in the arid Zarand region, Iran: comparing logistic regression approaches to predict diagnostic horizons and soil types

Hossein Khademi, Peter Finke, Shamsollah Ayoubi, 2012 .

COMPARISON OF ARTIFICIAL NEURAL NETWORK (ANN) AND MULTIVARIATE LINEAR REGRESSION (MLR) MODELS TO PREDICT SOIL ORGANIC CARBON USING DIGITAL TERRAIN ANALYSIS (CASE STUDY: ZARGHAM ABAD SEMIROM, ISFAHAN PROVIANCE)

H. Khademi, S. Ayoubi, A. Shahri, 2011 .

Chronostratigraphic distribution and genesis of palygorskite in Tertiary sediments of the Isfahan region, central Iran

H. Khademi, S. Ayoubi, J. Arocena, 2012, Clay Minerals.

The ANDROMEDA prospective cohort study: predictive value of combined criteria to tailor breast cancer screening and new opportunities from circulating markers: study protocol

E. Petracci, P. Ostano, A. Ponti, 2017, BMC Cancer.

Predicting rainfed wheat quality and quantity by artificial neural network using terrain and soil characteristics

A. Jalalian, H. Khademi, S. Ayoubi, 2010 .