Neural networks in climate spatialization and their application in the agricultural zoning of climate risk for sunflower in different sowing dates-Reference-Cited by-同舟云学术

Neural networks in climate spatialization and their application in the agricultural zoning of climate risk for sunflower in different sowing dates

Published:2019-01-16 Issue:11 Volume:65 Page:1477-1492
ISSN:0365-0340
Container-title:Archives of Agronomy and Soil Science
language:en
Short-container-title:Archives of Agronomy and Soil Science

Author:

Aparecido Lucas Eduardo de Oliveira¹^ORCID,Moraes José Reinaldo da Silva Cabral de²,Rolim Glauco de Souza²,Martorano Lucieta Guerreiro³,Meneses Kamila Cunha de²,Valeriano Taynara Tuany Borges²

Affiliation:

1. Science and Technology of Mato Grosso do Sul - Campus of Naviraí, IFMS - Federal Institute of Education, Naviraí, Brasil

2. Department of Exact Sciences, UNESP – São Paulo State University, Jaboticabal, Brazil

3. Embrapa Eastern Amazon Trav, Santarém, Brasil

Publisher

Informa UK Limited

Subject

Soil Science,Agronomy and Crop Science

Link

https://www.tandfonline.com/doi/pdf/10.1080/03650340.2019.1566715

Reference31 articles.

1. REFERENCE EVAPOTRANSPIRATION FORECASTING BY ARTIFICIAL NEURAL NETWORKS

2. Climatic potential for summer and winter wine production

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