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| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 02270naa a2200337 4500 | |
| 001 | oai:DiVA.org:uu-366012 | |
| 003 | SwePub | |
| 008 | 181115s2017 | |||||||||||000 ||eng| | |
| 024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-3660122 URI |
| 024 | 7 | a https://doi.org/10.1002/met.16502 DOI |
| 040 | a (SwePub)uu | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a ref2 swepub-contenttype |
| 072 | 7 | a art2 swepub-publicationtype |
| 100 | 1 | a Kurian, Nisha4 aut |
| 245 | 1 0 | a A soft-computing ensemble approach (SEA) to forecast Indian summer monsoon rainfall |
| 264 | c 2017-03-07 | |
| 264 | 1 | b Wiley-Blackwell,c 2017 |
| 338 | a print2 rdacarrier | |
| 520 | a Agriculture is the backbone of the Indian economy and contributes ∼16% of gross domestic product and about10% of total exports. Hence, accurate and timely forecasting of monthly Indian summer monsoon rainfall is very much in demand for economic planning and agricultural practices. Several methods and models, comprising dynamic and statistical models and combinations of the two, exist for monsoon forecasting. Here, a multi-model ensemble approach, combined within the artificial neural networking technique, was used to develop a soft-computing ensemble algorithm (SEA) to forecast the monthly and seasonal rainfall over the Indian subcontinent. Forecasts using January to May initial conditions along with observations during 1982–2014 were used to develop the model. The SEA compares well with observations | |
| 650 | 7 | a NATURVETENSKAPx Geovetenskap och miljövetenskap0 (SwePub)1052 hsv//swe |
| 650 | 7 | a NATURAL SCIENCESx Earth and Related Environmental Sciences0 (SwePub)1052 hsv//eng |
| 700 | 1 | a Thandlam, Venugopalu Department of Physics, Novosibirsk State University, Russia4 aut0 (Swepub:uu)venth596 |
| 700 | 1 | a Singh, Jatin4 aut |
| 700 | 1 | a Ali, M. M.4 aut |
| 710 | 2 | a Department of Physics, Novosibirsk State University, Russia4 org |
| 773 | 0 | t Meteorological Applicationsd : Wiley-Blackwellg 24:2, s. 308-314q 24:2<308-314x 1350-4827x 1469-8080 |
| 856 | 4 | u https://rmets.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/met.1650 |
| 856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-366012 |
| 856 | 4 8 | u https://doi.org/10.1002/met.1650 |
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