Artificial neural networks and multiple linear regression as potential methods for modeling seed yield of safflower (Carthamus tinctorius L.)-Reference-Cited by-同舟云学术

Artificial neural networks and multiple linear regression as potential methods for modeling seed yield of safflower (Carthamus tinctorius L.)

Published:2019-01 Issue: Volume:127 Page:185-194
ISSN:0926-6690
Container-title:Industrial Crops and Products
language:en
Short-container-title:Industrial Crops and Products

Author:

Abdipour Moslem^ORCID,Younessi-Hmazekhanlu Mehdi,Ramazani Seyyed Hamid Reza,omidi Amir hassan

Publisher

Elsevier BV

Subject

Agronomy and Crop Science

Reference90 articles.

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4. Modeling oil content of sesame (Sesamum indicum L.) using artificial neural network and multiple linear regression approaches;Abdipour;J. Am. Oil Chem. Soc.,2018

5. Modeling root length density of field grown potatoes under different irrigation strategies and soil textures using artificial neural networks;Ahmadi;Field Crops Res.,2014

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