Kaundal, Rakesh and Kapoor, Amar S and Raghava, G.P.S. (2006) Machine learning techniques in disease forecasting: a case study on rice blast prediction. BMC bioinformatics, 7. p. 485. ISSN 1471-2105
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Official URL: http://www.biomedcentral.com/1471-2105/7/485
Abstract
Our case study demonstrated that SVM is better than existing machine learning techniques and conventional REG approaches in forecasting plant diseases. In this direction, we have also developed a SVM-based web server for rice blast prediction, a first of its kind worldwide, which can help the plant science community and farmers in their decision making process. The server is freely available at http://www.imtech.res.in/raghava/rbpred/.
Item Type: | Article |
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Additional Information: | OPEN ACCESS |
Subjects: | Q Science > QR Microbiology |
Depositing User: | Dr. K.P.S.Sengar |
Date Deposited: | 09 Jan 2012 04:21 |
Last Modified: | 09 Jan 2012 04:21 |
URI: | http://crdd.osdd.net/open/id/eprint/131 |
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