Crop Prediction Using Feature Selection And Ensemble Techniques.
Research in agriculture is expanding. Agriculture relies heavily on environmental and soil aspects, including temperature, humidity, and rainfall to anticipate crops. In the past, farmers had control over the selection of the crop to be grown, monitoring the development and timing of its harvest. Th...
| Publicado en: | Journal of Namibian Studies Vol. 33; pp. 3211 - 3227 |
|---|---|
| Autores principales: | , |
| Formato: | Artículo |
| Publicado: |
Society of Cultural Studies & Social Sciences
2023 Supplement
|
| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=hlh&AN=172998429&site=ehost-live header: @attributes: shortDbName: hlh uiTerm: 172998429 longDbName: Humanities International Complete uiTag: AN controlInfo: bkinfo: jinfo: jid: 18635954 G5EZ jtl: Journal of Namibian Studies issn: 18635954 maglogo: N pubinfo: dt: 2023 Supplement vid: 33 pid: 92471 pub: Society of Cultural Studies & Social Sciences artinfo: ui: 172998429 ppf: 3211 ppct: 16 formats: tig: atl: Crop Prediction Using Feature Selection And Ensemble Techniques. aug: au: Neelufar, S. Siva Kumar, A. P. affil: M.Tech Scholar Department of CSE JNTUA College of Engineering Ananthapuramu, A.P, India. Professor Department Of Cse Jntua College of Engineering Ananthapuramu, India. su: Feature selection Random forest algorithms Environmental soil science Support vector machines Agricultural forecasts Weed competition Growing season sug: subj: Feature selection Random forest algorithms Environmental soil science Support vector machines Agricultural forecasts Weed competition Growing season keyword: Crop Prediction Decision trees Ensemble Techniques Random forest and Feature selection ab: Research in agriculture is expanding. Agriculture relies heavily on environmental and soil aspects, including temperature, humidity, and rainfall to anticipate crops. In the past, farmers had control over the selection of the crop to be grown, monitoring the development and timing of its harvest. The difficult process of forecasting crops in agriculture has resulted in the creation and testing of several models. such as Classification Techniques of Machine learning. The purpose of this research is to enhance the accuracy of the crop forecast by employing Ensemble Techniques. Ensembling In comparison to the current classification techniques, the Decision Tree, Support Vector Machine, and Random Forest algorithms perform better and provide greater accuracy. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: Y dt: @attributes: year: 2023 holdings: @attributes: islocal: N |
|---|