MODELO DE RED NEURONAL ARTIFICIAL PARA LA PREDICCIÓN DEL FENÓMENO “EL NIÑO” EN LA REGIÓN DE PIURA (PERÚ)

Oscar J.M. Peña Cáceres; Manuel A. More More; Rudy Espinoza Nima; Henry Silva Marchan

doi:10.37467/revtechno.v13.4815

MODELO DE RED NEURONAL ARTIFICIAL PARA LA PREDICCIÓN DEL FENÓMENO “EL NIÑO” EN LA REGIÓN DE PIURA (PERÚ)

Oscar J.M. Peña Cáceres, Manuel A. More More, Rudy Espinoza Nima, Henry Silva Marchan

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

4 Citas (Scopus)

Resumen

El Phenomenon El Niño is an event of climatic origin. In 2017 this event will impact the region Piura, Peru. The heavy rainfall generated the overflow of the Piura River that affects the districts of Piura, Castilla, Catacaos and Cura Mori. The objective of the study is to identify the most influential variables and to have a model that predicts the occurrence of the El Niño Phenomenon in the Piura region, through the use of Artificial Neuronal Networks. The results indicate that the Surface Temperature of the Sea is the most influential variable. The model has an accuracy of 82% accuracy.

Título traducido de la contribución	Artificial neural network model for the prediction of the "El Niño" phenomenon in the region of Piura (Peru)
Idioma original	Español
Publicación	TECHNO Review. International Technology, Science and Society Review / Revista Internacional de Tecnología, Ciencia y Sociedad
Volumen	13
N.º	4
DOI	https://doi.org/10.37467/revtechno.v13.4815
Estado	Publicada - 2023
Publicado de forma externa	Sí

Nota bibliográfica

Publisher Copyright:
© GKA Ediciones, authors.

Palabras clave

Artificial Neural Network
Phenomenon “El Niño”
Prediction
Región Piura
Sea Surface Temperature

Acceder al documento

10.37467/revtechno.v13.4815

Otros archivos y enlaces

Enlace a la publicación en Scopus

Citar esto

Peña Cáceres, O. J. M., More More, M. A., Nima, R. E., & Marchan, H. S. (2023). MODELO DE RED NEURONAL ARTIFICIAL PARA LA PREDICCIÓN DEL FENÓMENO “EL NIÑO” EN LA REGIÓN DE PIURA (PERÚ). TECHNO Review. International Technology, Science and Society Review / Revista Internacional de Tecnología, Ciencia y Sociedad, 13(4). https://doi.org/10.37467/revtechno.v13.4815

@article{9e40a40503b9402c895e5f990c59918a,

title = "MODELO DE RED NEURONAL ARTIFICIAL PARA LA PREDICCI{\'O}N DEL FEN{\'O}MENO “EL NI{\~N}O” EN LA REGI{\'O}N DE PIURA (PER{\'U})",

abstract = "El Phenomenon El Ni{\~n}o is an event of climatic origin. In 2017 this event will impact the region Piura, Peru. The heavy rainfall generated the overflow of the Piura River that affects the districts of Piura, Castilla, Catacaos and Cura Mori. The objective of the study is to identify the most influential variables and to have a model that predicts the occurrence of the El Ni{\~n}o Phenomenon in the Piura region, through the use of Artificial Neuronal Networks. The results indicate that the Surface Temperature of the Sea is the most influential variable. The model has an accuracy of 82% accuracy.",

keywords = "Artificial Neural Network, Phenomenon “El Ni{\~n}o”, Prediction, Regi{\'o}n Piura, Sea Surface Temperature",

author = "{Pe{\~n}a C{\'a}ceres}, {Oscar J.M.} and {More More}, {Manuel A.} and Nima, {Rudy Espinoza} and Marchan, {Henry Silva}",

note = "Publisher Copyright: {\textcopyright} GKA Ediciones, authors.",

year = "2023",

doi = "10.37467/revtechno.v13.4815",

language = "Espa{\~n}ol",

volume = "13",

journal = "TECHNO Review. International Technology, Science and Society Review / Revista Internacional de Tecnolog{\'i}a, Ciencia y Sociedad",

issn = "2695-9933",

publisher = "Eagora Science",

number = "4",

}

Peña Cáceres, OJM, More More, MA, Nima, RE & Marchan, HS 2023, 'MODELO DE RED NEURONAL ARTIFICIAL PARA LA PREDICCIÓN DEL FENÓMENO “EL NIÑO” EN LA REGIÓN DE PIURA (PERÚ)', TECHNO Review. International Technology, Science and Society Review / Revista Internacional de Tecnología, Ciencia y Sociedad, vol. 13, n.º 4. https://doi.org/10.37467/revtechno.v13.4815

MODELO DE RED NEURONAL ARTIFICIAL PARA LA PREDICCIÓN DEL FENÓMENO “EL NIÑO” EN LA REGIÓN DE PIURA (PERÚ). / Peña Cáceres, Oscar J.M.; More More, Manuel A.; Nima, Rudy Espinoza et al.
En: TECHNO Review. International Technology, Science and Society Review / Revista Internacional de Tecnología, Ciencia y Sociedad, Vol. 13, N.º 4, 2023.

Producción científica: Contribución a una revista › Artículo › revisión exhaustiva

TY - JOUR

T1 - MODELO DE RED NEURONAL ARTIFICIAL PARA LA PREDICCIÓN DEL FENÓMENO “EL NIÑO” EN LA REGIÓN DE PIURA (PERÚ)

AU - Peña Cáceres, Oscar J.M.

AU - More More, Manuel A.

AU - Nima, Rudy Espinoza

AU - Marchan, Henry Silva

PY - 2023

Y1 - 2023

N2 - El Phenomenon El Niño is an event of climatic origin. In 2017 this event will impact the region Piura, Peru. The heavy rainfall generated the overflow of the Piura River that affects the districts of Piura, Castilla, Catacaos and Cura Mori. The objective of the study is to identify the most influential variables and to have a model that predicts the occurrence of the El Niño Phenomenon in the Piura region, through the use of Artificial Neuronal Networks. The results indicate that the Surface Temperature of the Sea is the most influential variable. The model has an accuracy of 82% accuracy.

AB - El Phenomenon El Niño is an event of climatic origin. In 2017 this event will impact the region Piura, Peru. The heavy rainfall generated the overflow of the Piura River that affects the districts of Piura, Castilla, Catacaos and Cura Mori. The objective of the study is to identify the most influential variables and to have a model that predicts the occurrence of the El Niño Phenomenon in the Piura region, through the use of Artificial Neuronal Networks. The results indicate that the Surface Temperature of the Sea is the most influential variable. The model has an accuracy of 82% accuracy.

KW - Artificial Neural Network

KW - Phenomenon “El Niño”

KW - Prediction

KW - Región Piura

KW - Sea Surface Temperature

UR - http://www.scopus.com/inward/record.url?scp=85150380924&partnerID=8YFLogxK

U2 - 10.37467/revtechno.v13.4815

DO - 10.37467/revtechno.v13.4815

M3 - Artículo

AN - SCOPUS:85150380924

SN - 2695-9933

VL - 13

JO - TECHNO Review. International Technology, Science and Society Review / Revista Internacional de Tecnología, Ciencia y Sociedad

JF - TECHNO Review. International Technology, Science and Society Review / Revista Internacional de Tecnología, Ciencia y Sociedad

IS - 4

ER -

MODELO DE RED NEURONAL ARTIFICIAL PARA LA PREDICCIÓN DEL FENÓMENO “EL NIÑO” EN LA REGIÓN DE PIURA (PERÚ)

Resumen

Nota bibliográfica

Palabras clave

Acceder al documento

Otros archivos y enlaces

Huella

Citar esto