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Temperature prediction using a Neofuzzy neuron approach

In this paper it?s presented a temperature prediction application using a modified neofuzzy neuron-based approach. This approach is an easy and accurate method for obtaining prediction results using climatic measurements from the previous days. The variables used for building the model are Temperatu...

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Autor Principal: Rivas, Francklin
Formato: Artículos
Lenguaje:eng
Publicado: 2017
Materias:
NEOFUZZY NEURON
TEMPERATURE PREDICTION
FUZZY LOGIC
Acceso en línea:http://repositorio.educacionsuperior.gob.ec/handle/28000/4075
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spelling oai:localhost:28000-40752017-04-13T16:37:36Z Temperature prediction using a Neofuzzy neuron approach Rivas, Francklin NEOFUZZY NEURON TEMPERATURE PREDICTION FUZZY LOGIC In this paper it?s presented a temperature prediction application using a modified neofuzzy neuron-based approach. This approach is an easy and accurate method for obtaining prediction results using climatic measurements from the previous days. The variables used for building the model are Temperature, Humidity, Dew Point, Wind speed, Pressure, Rain and Solar Radiation. It?s also presented the obtained results for temperature prediction in Ibarra, Ecuador using three years data. http://www.wseas.us/e-library/conferences/2016/barcelona/SECEA/SECEA-22.pdf 2017-04-12T19:00:18Z 2017-04-12T19:00:18Z 2015 article Rivas Echeverr?a, Francklin. et al. (2015). Temperature prediction using a Neofuzzy neuron approach. WSEAS Transactions on Systems and Control. Grecia. 978-1-61804-365-8 http://repositorio.educacionsuperior.gob.ec/handle/28000/4075 eng openAccess http://creativecommons.org/licenses/by-nc-sa/3.0/ec/
institution SENESCYT
collection Repositorio SENESCYT
biblioteca Biblioteca Senescyt
language eng
format Artículos
topic NEOFUZZY NEURON
TEMPERATURE PREDICTION
FUZZY LOGIC
spellingShingle NEOFUZZY NEURON
TEMPERATURE PREDICTION
FUZZY LOGIC
Rivas, Francklin
Temperature prediction using a Neofuzzy neuron approach
description In this paper it?s presented a temperature prediction application using a modified neofuzzy neuron-based approach. This approach is an easy and accurate method for obtaining prediction results using climatic measurements from the previous days. The variables used for building the model are Temperature, Humidity, Dew Point, Wind speed, Pressure, Rain and Solar Radiation. It?s also presented the obtained results for temperature prediction in Ibarra, Ecuador using three years data.
author Rivas, Francklin
author_facet Rivas, Francklin
author_sort Rivas, Francklin
title Temperature prediction using a Neofuzzy neuron approach
title_short Temperature prediction using a Neofuzzy neuron approach
title_full Temperature prediction using a Neofuzzy neuron approach
title_fullStr Temperature prediction using a Neofuzzy neuron approach
title_full_unstemmed Temperature prediction using a Neofuzzy neuron approach
title_sort temperature prediction using a neofuzzy neuron approach
publishDate 2017
url http://repositorio.educacionsuperior.gob.ec/handle/28000/4075
_version_ 1634995217885036544
score 11,871979

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