Artificial neural network

Artificial neural networks to estimate, artichoke’s antioxidant components evaluation based on the easily available soil properties

Azadeh Alizadeh

Int. J. Biosci.16( 6), 98-120, June 2020.

DOI: http://dx.doi.org/10.12692/ijb/16.6.98-120

Key: Antioxidant Artichoke Artificial neural network Function Medicinal plants Soil texture

Prediction of the desertification variation trend in Haj Ali Gholi desert basin for 2030 and 2045

Abbas Alipoir, Mostafa Hashemi, Sajad Bagheri, Abbas Najafi, Ali Mohammadi

J. Bio. Env. Sci.11( 1), 14-24, July 2017.

Key: Artificial neural network Desertification variation Landsat images Vegetation index

Prognostication of total greenhouse gas emissions and economic indices for hazelnut production in Guilan province, Iran

Alireza Sabzevari, Ashkan Nabavi-Pelesaraei

J. Bio. Env. Sci.6( 2), 132-140, February 2015.

Key: Artificial neural network Economic indices GHG emission Hazelnut Sensitivity analysis

Modeling the compression index for fine soils using an intelligent method

Seyed Mahmood Kashefipour, Mehdi Daryaee

J. Bio. Env. Sci.5( 5), 197-204, November 2014.

Key: Artificial neural network Clay soils Compression coefficient Soil physical properties

Prediction of yield and economic indices for tangerine production using artificial neural networks based on energy consumption

Ashkan Nabavi-Pelesaraei, Farhad Fatehi, Asghar Mahmoudi

Int. J. Agron. Agri. Res.4( 5), 57-64, May 2014.

Key: Artificial neural network Economic indices Energy Modeling Tangerine yield

Modeling sediment yield using artificial neural network and multiple linear regression methods

Lida Eisazadeh, Reza Sokouti, Mehdi Homaee, Ebrahim Pazira

Int. J. Biosci.3( 9), 116-122, September 2013.

DOI: http://dx.doi.org/10.12692/ijb/3.9.116-122

Key: Artificial neural network Regression Sediment estimation Sediment-retention reservoirs

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