Inteligencia artificial para la producción agropecuaria

Autores:
Moreno P., Diego Fernando
Tipo de recurso:
Article of journal
Fecha de publicación:
2024
Institución:
Universidad Pedagógica y Tecnológica de Colombia
Repositorio:
RiUPTC: Repositorio Institucional UPTC
Idioma:
OAI Identifier:
oai:repositorio.uptc.edu.co:001/18913
Acceso en línea:
https://repositorio.uptc.edu.co/handle/001/18913
https://doi.org/10.19053/uptc.01228420.v21.n2.2024.19386
Palabra clave:
Machine Learning
Deep Learning
Toma de decisiones
Recursos naturales
Rendimiento
Productividad
Inteligencia artificial
Decision-making
Natural resources
Yield
Productivity
Artificial intelligence
Rights
openAccess
License
Diego Fernando Moreno - 2024
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spelling Moreno P., Diego Fernando2024-07-01 00:00:002026-04-16T17:14:36Z2024-07-01 00:00:002024-07-010122-8420https://repositorio.uptc.edu.co/handle/001/1891310.19053/uptc.01228420.v21.n2.2024.193862539-0899https://doi.org/10.19053/uptc.01228420.v21.n2.2024.19386application/pdfUniversidad Pedagógica y Tecnológica de ColombiaDiego Fernando Moreno - 2024http://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/19386Machine LearningDeep LearningToma de decisionesRecursos naturalesRendimientoProductividadInteligencia artificialDecision-makingNatural resourcesYieldProductivityArtificial intelligenceInteligencia artificial para la producción agropecuariaArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/coar/version/c_970fb48d4fbd8a85Cao, L. (2017). Data Science: A Comprehensive Overview. ACM Computing Surveys (CSUR), 50(3), 43.Chlingaryan, A., Sukkarieh, S., & Whelan, B. (2018). Machine learning approachesfor crop yield prediction and nitrogen status estimation in precision agriculture: A review. Computers and Electronics in Agriculture, 151, 61-69.Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255-260.LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553),436-444.Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. Sensors, 18(8), 2674.Russell, S., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach. 3rd Edition.Pearson.1938621938621Ciencia y Agriculturahttps://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/download/19386/15536PublicationOREORE.xmltext/xml2527https://repositorio.uptc.edu.co/bitstreams/3f4c0d52-92d1-445b-8373-c8590e73cef8/downloada84dea8bb690d91400b6ad67f54606eaMD51falseAnonymousREAD001/18913oai:repositorio.uptc.edu.co:001/189132026-10-28 07:36:47.366http://creativecommons.org/licenses/by/4.0metadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCbdigital@metabiblioteca.com
dc.title.es-ES.fl_str_mv Inteligencia artificial para la producción agropecuaria
title Inteligencia artificial para la producción agropecuaria
spellingShingle Inteligencia artificial para la producción agropecuaria
Machine Learning
Deep Learning
Toma de decisiones
Recursos naturales
Rendimiento
Productividad
Inteligencia artificial
Decision-making
Natural resources
Yield
Productivity
Artificial intelligence
title_short Inteligencia artificial para la producción agropecuaria
title_full Inteligencia artificial para la producción agropecuaria
title_fullStr Inteligencia artificial para la producción agropecuaria
title_full_unstemmed Inteligencia artificial para la producción agropecuaria
title_sort Inteligencia artificial para la producción agropecuaria
dc.creator.fl_str_mv Moreno P., Diego Fernando
dc.contributor.author.eng.fl_str_mv Moreno P., Diego Fernando
dc.subject.none.fl_str_mv Machine Learning
Deep Learning
Toma de decisiones
Recursos naturales
Rendimiento
Productividad
Inteligencia artificial
Decision-making
Natural resources
Yield
Productivity
Artificial intelligence
topic Machine Learning
Deep Learning
Toma de decisiones
Recursos naturales
Rendimiento
Productividad
Inteligencia artificial
Decision-making
Natural resources
Yield
Productivity
Artificial intelligence
publishDate 2024
dc.date.accessioned.none.fl_str_mv 2024-07-01 00:00:00
2026-04-16T17:14:36Z
dc.date.available.none.fl_str_mv 2024-07-01 00:00:00
dc.date.issued.none.fl_str_mv 2024-07-01
dc.type.spa.fl_str_mv Artículo de revista
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dc.identifier.doi.none.fl_str_mv 10.19053/uptc.01228420.v21.n2.2024.19386
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url https://repositorio.uptc.edu.co/handle/001/18913
https://doi.org/10.19053/uptc.01228420.v21.n2.2024.19386
dc.language.iso.none.fl_str_mv
language_invalid_str_mv
dc.relation.references.none.fl_str_mv Cao, L. (2017). Data Science: A Comprehensive Overview. ACM Computing Surveys (CSUR), 50(3), 43.
Chlingaryan, A., Sukkarieh, S., & Whelan, B. (2018). Machine learning approachesfor crop yield prediction and nitrogen status estimation in precision agriculture: A review. Computers and Electronics in Agriculture, 151, 61-69.
Jordan, M. I., & Mitchell, T. M. (2015). Machine learning: Trends, perspectives, and prospects. Science, 349(6245), 255-260.
LeCun, Y., Bengio, Y., & Hinton, G. (2015). Deep learning. Nature, 521(7553),436-444.
Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. Sensors, 18(8), 2674.
Russell, S., & Norvig, P. (2016). Artificial Intelligence: A Modern Approach. 3rd Edition.Pearson.
dc.relation.citationendpage.none.fl_str_mv 19386
dc.relation.citationissue.eng.fl_str_mv 2
dc.relation.citationstartpage.none.fl_str_mv 19386
dc.relation.citationvolume.eng.fl_str_mv 21
dc.relation.ispartofjournal.eng.fl_str_mv Ciencia y Agricultura
dc.relation.bitstream.none.fl_str_mv https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/download/19386/15536
dc.rights.none.fl_str_mv Diego Fernando Moreno - 2024
dc.rights.uri.none.fl_str_mv http://creativecommons.org/licenses/by/4.0
dc.rights.accessrights.none.fl_str_mv info:eu-repo/semantics/openAccess
dc.rights.creativecommons.none.fl_str_mv This work is licensed under a Creative Commons Attribution 4.0 International License.
dc.rights.coar.none.fl_str_mv http://purl.org/coar/access_right/c_abf2
rights_invalid_str_mv Diego Fernando Moreno - 2024
http://creativecommons.org/licenses/by/4.0
This work is licensed under a Creative Commons Attribution 4.0 International License.
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.mimetype.none.fl_str_mv application/pdf
dc.publisher.eng.fl_str_mv Universidad Pedagógica y Tecnológica de Colombia
dc.source.none.fl_str_mv https://revistas.uptc.edu.co/index.php/ciencia_agricultura/article/view/19386
institution Universidad Pedagógica y Tecnológica de Colombia
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