KRISHI
ICAR RESEARCH DATA REPOSITORY FOR KNOWLEDGE MANAGEMENT
(An Institutional Publication and Data Inventory Repository)
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Please use this identifier to cite or link to this item:
http://krishi.icar.gov.in/jspui/handle/123456789/40764
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Director ICAR-IASRI | en_US |
dc.date.accessioned | 2020-09-02T09:33:58Z | - |
dc.date.available | 2020-09-02T09:33:58Z | - |
dc.date.issued | 2018-04-01 | - |
dc.identifier.citation | Not Available | en_US |
dc.identifier.issn | Not Available | - |
dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/40764 | - |
dc.description | Not Available | en_US |
dc.description.abstract | An attempt has been made to develop hybrid models by combining time series models viz., Auto-Regressive Integrated Moving Average i.e. ARIMA / ARIMA with eXplanatory variables i.e. ARIMAX and machine learning techniques viz., Artificial Neural Networks (ANN) / Support Vector Machines (SVM) for forecasting rice yield using weather based covariates (explanatory variables) namely, minimum temperature, maximum temperature and rainfall for Aligarh and Meerut districts of Uttar Pradesh. For this, time series has been considered as a function of linear and nonlinear components and ARIMA/ ARIMAX models were employed to fit and predict the linear component while the residuals have been predicted employing ANN/ SVM models. Eventually, the predicted linear and nonlinear components are combined to obtain aggregate prediction. The proposed hybrid approach was found to be better than the traditional time series models in terms of their forecasting performance. | en_US |
dc.description.sponsorship | Not Available | en_US |
dc.language.iso | English | en_US |
dc.publisher | ICAR-IASRI, New Delhi | en_US |
dc.relation.ispartofseries | Not Available; | - |
dc.subject | Agricultural Statistics | en_US |
dc.subject | Design of Experiments | en_US |
dc.subject | Sample Surveys | en_US |
dc.subject | Statistical Genetics | en_US |
dc.subject | Forecasting Techniques | en_US |
dc.subject | Bioinformatics | en_US |
dc.subject | Computer Applications | en_US |
dc.title | ICAR-IASRI Newsletter, Jan-March, 2018 | en_US |
dc.title.alternative | Not Available | en_US |
dc.type | News Letter | en_US |
dc.publication.projectcode | Not Available | en_US |
dc.publication.journalname | Not Available | en_US |
dc.publication.volumeno | 22(4) | en_US |
dc.publication.pagenumber | 1-36 | en_US |
dc.publication.divisionUnit | Not Available | en_US |
dc.publication.sourceUrl | https://iasri.icar.gov.in/wp-content/uploads/2019/12/jan-march2018.pdf | en_US |
dc.publication.authorAffiliation | ICAR::Indian Agricultural Statistics Research Institute | en_US |
dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
dc.publication.naasrating | Not Available | - |
Appears in Collections: | AEdu-IASRI-Publication |
Files in This Item:
File | Description | Size | Format | |
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Newsletter jan-march2018.pdf | 1.65 MB | Adobe PDF | View/Open |
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