dor_id: 4142994

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590.#.#.d: Los artículos enviados a la revista "Journal of Applied Research and Technology", se juzgan por medio de un proceso de revisión por pares

510.0.#.a: Scopus, Directory of Open Access Journals (DOAJ); Sistema Regional de Información en Línea para Revistas Científicas de América Latina, el Caribe, España y Portugal (Latindex); Indice de Revistas Latinoamericanas en Ciencias (Periódica); La Red de Revistas Científicas de América Latina y el Caribe, España y Portugal (Redalyc); Consejo Nacional de Ciencia y Tecnología (CONACyT); Google Scholar Citation

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650.#.4.x: Ingenierías

336.#.#.b: article

336.#.#.3: Artículo de Investigación

336.#.#.a: Artículo

351.#.#.6: https://jart.icat.unam.mx/index.php/jart

351.#.#.b: Journal of Applied Research and Technology

351.#.#.a: Artículos

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270.1.#.p: Revistas UNAM. Dirección General de Publicaciones y Fomento Editorial, UNAM en revistas@unam.mx

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850.#.#.a: Universidad Nacional Autónoma de México

856.4.0.u: https://jart.icat.unam.mx/index.php/jart/article/view/1698/992

100.1.#.a: Ajina, A.; K G, Jaya Christiyan; Bhat, Dheerej N; Saxena, Kanishk

524.#.#.a: Ajina, A., et al. (2023). Prediction of weather forecasting using artificial neural networks: Artificial Neural Networks: Machine Learning. Journal of Applied Research and Technology; Vol. 21 Núm. 2, 2023; 205-211. Recuperado de https://repositorio.unam.mx/contenidos/4142994

245.1.0.a: Prediction of weather forecasting using artificial neural networks: Artificial Neural Networks: Machine Learning

502.#.#.c: Universidad Nacional Autónoma de México

561.1.#.a: Instituto de Ciencias Aplicadas y Tecnología, UNAM

264.#.0.c: 2023

264.#.1.c: 2023-04-27

653.#.#.a: Artificial Neural Networks; AI Weather Forecast; Machine Learning; Weather Forecasting; Weather Prediction

506.1.#.a: La titularidad de los derechos patrimoniales de esta obra pertenece a las instituciones editoras. Su uso se rige por una licencia Creative Commons BY-NC-SA 4.0 Internacional, https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode.es, para un uso diferente consultar al responsable jurídico del repositorio por medio del correo electrónico gabriel.ascanio@icat.unam.mx

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520.3.#.a: Currently, weather forecasting is the most commonly discussed topic by social and economic activists. It is also attracting widespread interest due to its application in various public and private sectors that include marine, agriculture, air traffic, and forestry. Recent developments have made climatic changes happen at a dramatic rate, making old methods of weather forecasting less effective, more hectic, and unreliable. Improved and efficient methods of weather prediction are needed to overcome these difficulties. This paper describes machine learning approaches using artificial neural networks to predict the weather of a particular city and compare the different weather conditions in different cities. We demonstrate empirically that Artificial Neural Networks produce very low deviations hence providing nearly accurate results for weather forecasts on a daily basis.

773.1.#.t: Journal of Applied Research and Technology; Vol. 21 Núm. 2 (2023); 205-211

773.1.#.o: https://jart.icat.unam.mx/index.php/jart

022.#.#.a: ISSN electrónico: 2448-6736; ISSN: 1665-6423

310.#.#.a: Bimestral

300.#.#.a: Páginas: 205-211

264.#.1.b: Instituto de Ciencias Aplicadas y Tecnología, UNAM

doi: https://doi.org/10.22201/icat.24486736e.2023.21.2.1698

harvesting_date: 2023-11-08 13:10:00.0

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Artículo

Prediction of weather forecasting using artificial neural networks: Artificial Neural Networks: Machine Learning

Ajina, A.; K G, Jaya Christiyan; Bhat, Dheerej N; Saxena, Kanishk

Instituto de Ciencias Aplicadas y Tecnología, UNAM, publicado en Journal of Applied Research and Technology, y cosechado de Revistas UNAM

Licencia de uso

Procedencia del contenido

Cita

Ajina, A., et al. (2023). Prediction of weather forecasting using artificial neural networks: Artificial Neural Networks: Machine Learning. Journal of Applied Research and Technology; Vol. 21 Núm. 2, 2023; 205-211. Recuperado de https://repositorio.unam.mx/contenidos/4142994

Descripción del recurso

Autor(es)
Ajina, A.; K G, Jaya Christiyan; Bhat, Dheerej N; Saxena, Kanishk
Tipo
Artículo de Investigación
Área del conocimiento
Ingenierías
Título
Prediction of weather forecasting using artificial neural networks: Artificial Neural Networks: Machine Learning
Fecha
2023-04-27
Resumen
Currently, weather forecasting is the most commonly discussed topic by social and economic activists. It is also attracting widespread interest due to its application in various public and private sectors that include marine, agriculture, air traffic, and forestry. Recent developments have made climatic changes happen at a dramatic rate, making old methods of weather forecasting less effective, more hectic, and unreliable. Improved and efficient methods of weather prediction are needed to overcome these difficulties. This paper describes machine learning approaches using artificial neural networks to predict the weather of a particular city and compare the different weather conditions in different cities. We demonstrate empirically that Artificial Neural Networks produce very low deviations hence providing nearly accurate results for weather forecasts on a daily basis.
Tema
Artificial Neural Networks; AI Weather Forecast; Machine Learning; Weather Forecasting; Weather Prediction
Idioma
eng
ISSN
ISSN electrónico: 2448-6736; ISSN: 1665-6423

Enlaces