Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions
This paper investigates the potential of data mining techniques to predict daily soil temperatures at 5-100 cm depths for agricultural purposes. Climatic and soil temperature data from Isfahan province located in central Iran with a semi-arid climate was used for the modeling process. A subtractive...
- Autores:
-
Sattari, Mohammad Taghi
Dodangeh, Esmaeel
Abraham, John
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2017
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/63579
- Acceso en línea:
- https://repositorio.unal.edu.co/handle/unal/63579
http://bdigital.unal.edu.co/64025/
- Palabra clave:
- 55 Ciencias de la tierra / Earth sciences and geology
Soil temperature
Data mining
M5 tree model
ANFIS
ANN
Temperatura del suelo
minería de datos
modelo tipo árbol M5
- Rights
- openAccess
- License
- Atribución-NoComercial 4.0 Internacional
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Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions |
| title |
Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions |
| spellingShingle |
Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions 55 Ciencias de la tierra / Earth sciences and geology Soil temperature Data mining M5 tree model ANFIS ANN Temperatura del suelo minería de datos modelo tipo árbol M5 |
| title_short |
Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions |
| title_full |
Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions |
| title_fullStr |
Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions |
| title_full_unstemmed |
Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions |
| title_sort |
Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions |
| dc.creator.fl_str_mv |
Sattari, Mohammad Taghi Dodangeh, Esmaeel Abraham, John |
| dc.contributor.author.spa.fl_str_mv |
Sattari, Mohammad Taghi Dodangeh, Esmaeel Abraham, John |
| dc.subject.ddc.spa.fl_str_mv |
55 Ciencias de la tierra / Earth sciences and geology |
| topic |
55 Ciencias de la tierra / Earth sciences and geology Soil temperature Data mining M5 tree model ANFIS ANN Temperatura del suelo minería de datos modelo tipo árbol M5 |
| dc.subject.proposal.spa.fl_str_mv |
Soil temperature Data mining M5 tree model ANFIS ANN Temperatura del suelo minería de datos modelo tipo árbol M5 |
| description |
This paper investigates the potential of data mining techniques to predict daily soil temperatures at 5-100 cm depths for agricultural purposes. Climatic and soil temperature data from Isfahan province located in central Iran with a semi-arid climate was used for the modeling process. A subtractive clustering approach was used to identify the structure of the Adaptive Neuro-Fuzzy Inference System (ANFIS), and the result of the proposed approach was compared with artificial neural networks (ANNs) and an M5 tree model. Result suggests an improved performance using the ANFIS approach in predicting soil temperatures at various soil depths except at 100 cm. The performance of the ANNs and M5 tree models were found to be similar. However, the M5 tree model provides a simple linear relation to predicting the soil temperature for the data ranges used in this study. Error analyses of the predicted values at various depths show that the estimation error tends to increase with the depth. |
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2017 |
| dc.date.issued.spa.fl_str_mv |
2017-04-01 |
| dc.date.accessioned.spa.fl_str_mv |
2019-07-02T21:55:12Z |
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2019-07-02T21:55:12Z |
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Artículo de revista |
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http://purl.org/coar/resource_type/c_2df8fbb1 |
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info:eu-repo/semantics/article |
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http://purl.org/coar/resource_type/c_6501 |
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Text |
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ISSN: 2339-3459 |
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https://repositorio.unal.edu.co/handle/unal/63579 |
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http://bdigital.unal.edu.co/64025/ |
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ISSN: 2339-3459 |
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spa |
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spa |
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https://revistas.unal.edu.co/index.php/esrj/article/view/49829 |
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Universidad Nacional de Colombia Revistas electrónicas UN Earth Sciences Research Journal Earth Sciences Research Journal |
| dc.relation.references.spa.fl_str_mv |
Sattari, Mohammad Taghi and Dodangeh, Esmaeel and Abraham, John (2017) Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions. Earth Sciences Research Journal, 21 (2). pp. 85-93. ISSN 2339-3459 |
| dc.rights.spa.fl_str_mv |
Derechos reservados - Universidad Nacional de Colombia |
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http://purl.org/coar/access_right/c_abf2 |
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Atribución-NoComercial 4.0 Internacional |
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info:eu-repo/semantics/openAccess |
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openAccess |
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application/pdf |
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Universidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias - Departamento de Geociencia |
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Atribución-NoComercial 4.0 InternacionalDerechos reservados - Universidad Nacional de Colombiahttp://creativecommons.org/licenses/by-nc/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Sattari, Mohammad Taghi9f23e08c-d7e7-400b-9592-d999cbc41d09300Dodangeh, Esmaeel8e4c46e6-0eb5-44a5-8e44-c290ccce873d300Abraham, John34763fbb-46b7-448d-a6da-743591ae411f3002019-07-02T21:55:12Z2019-07-02T21:55:12Z2017-04-01ISSN: 2339-3459https://repositorio.unal.edu.co/handle/unal/63579http://bdigital.unal.edu.co/64025/This paper investigates the potential of data mining techniques to predict daily soil temperatures at 5-100 cm depths for agricultural purposes. Climatic and soil temperature data from Isfahan province located in central Iran with a semi-arid climate was used for the modeling process. A subtractive clustering approach was used to identify the structure of the Adaptive Neuro-Fuzzy Inference System (ANFIS), and the result of the proposed approach was compared with artificial neural networks (ANNs) and an M5 tree model. Result suggests an improved performance using the ANFIS approach in predicting soil temperatures at various soil depths except at 100 cm. The performance of the ANNs and M5 tree models were found to be similar. However, the M5 tree model provides a simple linear relation to predicting the soil temperature for the data ranges used in this study. Error analyses of the predicted values at various depths show that the estimation error tends to increase with the depth.Este artículo investiga el potencial de las técnicas de búsqueda y procesamiento de datos para pronosticar las temperaturas diarias del suelo a profundidades que van de los 5 a los 100 cm con propósitos agrícolas. Se utilizó la información climática y de temperatura del suelo de la provincia Ishafan, ubicada en el centro de Irán y de clima semiárido, para el proceso de modelamiento. Se usó un enfoque de agrupamiento sustractivo para identificar la estructura del Sistema de Inferencia Neuronal Difuso Adaptado (ANFIS, del inglés Adaptive Neuro-Fuzzy Inference System) y el resultado del acercamiento propuesto se comparó con redes artificiales neuronales (ANN) y el modelo tipo árbol M5. Los resultados sugieren un desempeño mejorado al usar el enfoque ANFIS en la predicción de las temperaturas del suelo en varios puntos de profundidad, excepto en los 100 cm. El desempeño de las redes artificiales neuronales y los modelos de árbol M5 fueron similares. Sin embargo, el modelo tipo árbol M5 provee una relación linear simple para predecir los rangos de datos de la temperatura del suelo utilizados en este estudio. Los análisis de error de los valores predichos a varias profundidades muestran que la estimación de error tiende a incrementarse con la profundidad.application/pdfspaUniversidad Nacional de Colombia - Sede Bogotá - Facultad de Ciencias - Departamento de Geocienciahttps://revistas.unal.edu.co/index.php/esrj/article/view/49829Universidad Nacional de Colombia Revistas electrónicas UN Earth Sciences Research JournalEarth Sciences Research JournalSattari, Mohammad Taghi and Dodangeh, Esmaeel and Abraham, John (2017) Estimation of daily soil temperature via data mining techniques in semi-arid climate conditions. Earth Sciences Research Journal, 21 (2). pp. 85-93. ISSN 2339-345955 Ciencias de la tierra / Earth sciences and geologySoil temperatureData miningM5 tree modelANFISANNTemperatura del suelominería de datosmodelo tipo árbol M5Estimation of daily soil temperature via data mining techniques in semi-arid climate conditionsArtículo de revistainfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1http://purl.org/coar/version/c_970fb48d4fbd8a85Texthttp://purl.org/redcol/resource_type/ARTORIGINAL49829-341135-1-PB.pdfapplication/pdf943804https://repositorio.unal.edu.co/bitstream/unal/63579/1/49829-341135-1-PB.pdfb4006ca175467ee66f90ba9a2f33bc24MD51THUMBNAIL49829-341135-1-PB.pdf.jpg49829-341135-1-PB.pdf.jpgGenerated Thumbnailimage/jpeg7441https://repositorio.unal.edu.co/bitstream/unal/63579/2/49829-341135-1-PB.pdf.jpg251f8a02633d81551450e7bfcde82a16MD52unal/63579oai:repositorio.unal.edu.co:unal/635792023-04-22 23:05:26.321Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.co |