TECHNICAL NOTE: SOFTWARE TO ESTIMATE AIR TEMPERATURE IN THE BRAZILIAN NORTHEASTERN REGION USING ARTIFICIAL NEURAL NETWORKS

Autores

  • Michel Castro Moreira
  • Roberto Avelino Cecílio

DOI:

https://doi.org/10.13083/reveng.v24i2.631

Palavras-chave:

artificial intelligence, interpolation, GIS, GTOPO30, climate modeling.

Resumo

Air temperature is one of the most important factors affecting vegetation and controlling key ecological processes. The objective of this study was to develop software using artificial neural networks (ANNs) for the estimation of air temperature in the Northeastern region in Brazil. The architectures, the activation functions of the artificial neurons and the free parameters of the ANNs were defined to build a mathematical function to represent the ANN. The mathematical function was implemented by using Borland Delphi© 7 with a graphic interface to facilitate the use of the software. The software developed was denominated netTemperatura NE. It allows making a quick and easy estimation of the minimum, mean and maximum air temperatures (monthly or annual) in the Northeastern region of Brazil as a function of geographical coordinates and surface elevation. It is also available for free downloading at http://nedtecsoftwares.webnode.com.br.

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Publicado

2016-07-01

Como Citar

Moreira, M. C., & Cecílio, R. A. (2016). TECHNICAL NOTE: SOFTWARE TO ESTIMATE AIR TEMPERATURE IN THE BRAZILIAN NORTHEASTERN REGION USING ARTIFICIAL NEURAL NETWORKS. Revista Engenharia Na Agricultura, 24(2), 164-171. https://doi.org/10.13083/reveng.v24i2.631

Edição

Seção

Mecanização Agrícola

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