Archive for | Artificial neural network

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

By: Lida Eisazadeh, Reza Sokouti, Mehdi Homaee, Ebrahim Pazira

Key Words:

• Artificial neural network
• Regression
• Sediment estimation
• Sediment-retention reservoirs

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

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

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

By: Ashkan Nabavi-Pelesaraei, Farhad Fatehi, Asghar Mahmoudi

Key Words:

• Artificial neural network
• Economic indices
• Energy
• Modeling
• Tangerine yield

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

Modeling the compression index for fine soils using an intelligent method

By: Seyed Mahmood Kashefipour, Mehdi Daryaee

Key Words:

• Artificial neural network
• Clay soils
• Compression coefficient
• Soil physical properties

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

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

By: Alireza Sabzevari, Ashkan Nabavi-Pelesaraei

Key Words:

• Artificial neural network
• Economic indices
• GHG emission
• Hazelnut
• Sensitivity analysis

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

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

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

Key Words:

• Artificial neural network
• Desertification variation
• Landsat images
• Vegetation index

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

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

By: Azadeh Alizadeh

Key Words:

• Antioxidant
• Artichoke
• Artificial neural network
• Function
• Medicinal plants
• Soil texture

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

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