An Artificial Neural Network Model to Predict the Phenology of Early-Maturing Soybean Varieties from Climatic Factors-Reference-Cited by-同舟云学术

An Artificial Neural Network Model to Predict the Phenology of Early-Maturing Soybean Varieties from Climatic Factors

Published:2020-01 Issue:1 Volume:65 Page:106-117
ISSN:0006-3509
Container-title:Biophysics
language:en
Short-container-title:BIOPHYSICS

Author:

Taratuhin O. D.,Novikova L. Yu.,Seferova I. V.,Gerasimova T. V.,Nuzhdin S. V.,Samsonova M. G.,Kozlov K. N.

Publisher

Pleiades Publishing Ltd

Subject

Biophysics

Link

https://link.springer.com/content/pdf/10.1134/S0006350920010200.pdf

Reference31 articles.

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2. J. E. Olesen, T.R. Carter, C.H. Diaz-Ambrona, et al., Eur. J. Agron. 34 (2), 96 (2011).

3. T. Carter and K. Makinen, Approaches to Climate Change Impact, Adaptation and Vulnerability Assessment: Towards a Classification Framework to Serve Decision-Making: MEDIATION 2.1 (Finnish Environment Institute, Helsinki, Finland, 2011).

4. A. D. Richardson, R. S. Anderson, M. Altaf Arain, et al., Global Change Biol. 18 (2) 566 (2012).

5. K. N. Kozlov, L. Yu. Novikova, I. V. Seferova, and M. G. Samsonova, Biophysics (Moscow) 63 (1), 136 (2018).

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