Big data classification using fuzzy logical concepts for paddy yield prediction
Descripción del Articulo
Time association data has been critical to the exploration field of paddy yield forecast. At durations the path of recent many years, countless flossy legitimate time arrangement. For this reason, this paper canters round searching forward to statistics esteems on a huge variety of flossy precept ca...
| Autores: | , , , , , |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2021 |
| Institución: | Universidad de Lima |
| Repositorio: | ULIMA-Institucional |
| Lenguaje: | inglés |
| OAI Identifier: | oai:repositorio.ulima.edu.pe:20.500.12724/19564 |
| Enlace del recurso: | https://hdl.handle.net/20.500.12724/19564 https://doi.org/10.48047/rigeo.11.05.326 |
| Nivel de acceso: | acceso abierto |
| Materia: | Fuzzy Logic Rice Big data Lógica difusa Arroz https://purl.org/pe-repo/ocde/ford#4.01.01 |
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Roca Cedeño, Jacinto AlexGarcía López, Yván JesúsNeira-Molina, HaroldMorales-Ortega, RobertoCombita-Niño, H.Choque Flores, LeopoldoGarcía López, Yván Jesús2024-01-11T15:50:28Z2024-01-11T15:50:28Z2021Roca Cedeño, J. A., García - López, Y. J., Choque Flores, L. Morales-Ortega, R. Neira-Molina, H. & Combita-Niño, H. (2021). Big data classification using fuzzy logical concepts for paddy yield prediction. Review of International Geographical Education Online, 11(5), 4482-4490. https://doi.org/10.48047/rigeo.11.05.3262146-0353https://hdl.handle.net/20.500.12724/19564Review of International Geographical Education Online0000000121541816https://doi.org/10.48047/rigeo.11.05.3262-s2.0-85117203811Time association data has been critical to the exploration field of paddy yield forecast. At durations the path of recent many years, countless flossy legitimate time arrangement. For this reason, this paper canters round searching forward to statistics esteems on a huge variety of flossy precept calculations. To clarify the approach in the course of gauging, the verifiable statistics of paddy yield. The method for acknowledgment used at some point of this exam can also be an extreme information grouping. The technique joins the coaching capacities of fake neural device with the human like data portrayal and clarification capacities of flossy precept frameworks and furthermore a trendy primarily based in maximum instances hold close framework. It's miles for the most half of used in Brobdingnagian expertise getting equipped applications. As we have a tendency to in all opportunity am aware, affiliation method of massive information teams the information into thousands of categories addicted to high-quality trends for additional getting equipped. We've got engineered up some other calculation to have an effect on the grouping by using flossy recommendations on this present fact informational index. Forecast of harvest yield is significant because of this on precisely meet marketplace conditions and legitimate company of rural sports coordinated towards enhance in yield. A number of obstacles, as an example, weather, bothers, biophysical and physio morphological highlights advantage their idea whereas determining the yield. It's in reality proper right here that the flossy precept becomes partner in Nursing important issue. This paper explains a shot to create flossy valid frameworks for paddy crop yield expectation.application/htmlengEskisehir Osmangazi UniversityTRurn:issn: 2146-0353info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/4.0/Repositorio Institucional - UlimaUniversidad de Limareponame:ULIMA-Institucionalinstname:Universidad de Limainstacron:ULIMAFuzzy LogicRiceBig dataLógica difusaArrozhttps://purl.org/pe-repo/ocde/ford#4.01.01Big data classification using fuzzy logical concepts for paddy yield predictioninfo:eu-repo/semantics/articleArtículo en ScopusPendientePendiente1520.500.12724/19564oai:repositorio.ulima.edu.pe:20.500.12724/195642024-11-08 16:16:06.877Repositorio Universidad de Limarepositorio@ulima.edu.pe |
| dc.title.en_EN.fl_str_mv |
Big data classification using fuzzy logical concepts for paddy yield prediction |
| title |
Big data classification using fuzzy logical concepts for paddy yield prediction |
| spellingShingle |
Big data classification using fuzzy logical concepts for paddy yield prediction Roca Cedeño, Jacinto Alex Fuzzy Logic Rice Big data Lógica difusa Arroz https://purl.org/pe-repo/ocde/ford#4.01.01 |
| title_short |
Big data classification using fuzzy logical concepts for paddy yield prediction |
| title_full |
Big data classification using fuzzy logical concepts for paddy yield prediction |
| title_fullStr |
Big data classification using fuzzy logical concepts for paddy yield prediction |
| title_full_unstemmed |
Big data classification using fuzzy logical concepts for paddy yield prediction |
| title_sort |
Big data classification using fuzzy logical concepts for paddy yield prediction |
| author |
Roca Cedeño, Jacinto Alex |
| author_facet |
Roca Cedeño, Jacinto Alex García López, Yván Jesús Neira-Molina, Harold Morales-Ortega, Roberto Combita-Niño, H. Choque Flores, Leopoldo |
| author_role |
author |
| author2 |
García López, Yván Jesús Neira-Molina, Harold Morales-Ortega, Roberto Combita-Niño, H. Choque Flores, Leopoldo |
| author2_role |
author author author author author |
| dc.contributor.other.none.fl_str_mv |
García López, Yván Jesús |
| dc.contributor.author.fl_str_mv |
Roca Cedeño, Jacinto Alex García López, Yván Jesús Neira-Molina, Harold Morales-Ortega, Roberto Combita-Niño, H. Choque Flores, Leopoldo |
| dc.subject.en_EN.fl_str_mv |
Fuzzy Logic Rice |
| topic |
Fuzzy Logic Rice Big data Lógica difusa Arroz https://purl.org/pe-repo/ocde/ford#4.01.01 |
| dc.subject.es_PE.fl_str_mv |
Big data Lógica difusa Arroz |
| dc.subject.ocde.none.fl_str_mv |
https://purl.org/pe-repo/ocde/ford#4.01.01 |
| description |
Time association data has been critical to the exploration field of paddy yield forecast. At durations the path of recent many years, countless flossy legitimate time arrangement. For this reason, this paper canters round searching forward to statistics esteems on a huge variety of flossy precept calculations. To clarify the approach in the course of gauging, the verifiable statistics of paddy yield. The method for acknowledgment used at some point of this exam can also be an extreme information grouping. The technique joins the coaching capacities of fake neural device with the human like data portrayal and clarification capacities of flossy precept frameworks and furthermore a trendy primarily based in maximum instances hold close framework. It's miles for the most half of used in Brobdingnagian expertise getting equipped applications. As we have a tendency to in all opportunity am aware, affiliation method of massive information teams the information into thousands of categories addicted to high-quality trends for additional getting equipped. We've got engineered up some other calculation to have an effect on the grouping by using flossy recommendations on this present fact informational index. Forecast of harvest yield is significant because of this on precisely meet marketplace conditions and legitimate company of rural sports coordinated towards enhance in yield. A number of obstacles, as an example, weather, bothers, biophysical and physio morphological highlights advantage their idea whereas determining the yield. It's in reality proper right here that the flossy precept becomes partner in Nursing important issue. This paper explains a shot to create flossy valid frameworks for paddy crop yield expectation. |
| publishDate |
2021 |
| dc.date.accessioned.none.fl_str_mv |
2024-01-11T15:50:28Z |
| dc.date.available.none.fl_str_mv |
2024-01-11T15:50:28Z |
| dc.date.issued.fl_str_mv |
2021 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article |
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Artículo en Scopus |
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article |
| dc.identifier.citation.es_PE.fl_str_mv |
Roca Cedeño, J. A., García - López, Y. J., Choque Flores, L. Morales-Ortega, R. Neira-Molina, H. & Combita-Niño, H. (2021). Big data classification using fuzzy logical concepts for paddy yield prediction. Review of International Geographical Education Online, 11(5), 4482-4490. https://doi.org/10.48047/rigeo.11.05.326 |
| dc.identifier.issn.none.fl_str_mv |
2146-0353 |
| dc.identifier.uri.none.fl_str_mv |
https://hdl.handle.net/20.500.12724/19564 |
| dc.identifier.journal.none.fl_str_mv |
Review of International Geographical Education Online |
| dc.identifier.isni.none.fl_str_mv |
0000000121541816 |
| dc.identifier.doi.none.fl_str_mv |
https://doi.org/10.48047/rigeo.11.05.326 |
| dc.identifier.scopusid.none.fl_str_mv |
2-s2.0-85117203811 |
| identifier_str_mv |
Roca Cedeño, J. A., García - López, Y. J., Choque Flores, L. Morales-Ortega, R. Neira-Molina, H. & Combita-Niño, H. (2021). Big data classification using fuzzy logical concepts for paddy yield prediction. Review of International Geographical Education Online, 11(5), 4482-4490. https://doi.org/10.48047/rigeo.11.05.326 2146-0353 Review of International Geographical Education Online 0000000121541816 2-s2.0-85117203811 |
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https://hdl.handle.net/20.500.12724/19564 https://doi.org/10.48047/rigeo.11.05.326 |
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eng |
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eng |
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openAccess |
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https://creativecommons.org/licenses/by-nc-sa/4.0/ |
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application/html |
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Eskisehir Osmangazi University |
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TR |
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Eskisehir Osmangazi University |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).