| Records |
| Author |
Ipcc |
Title  |
Summary for Policymakers |
Type |
Book Chapter |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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| Volume |
Climate Change 2014: Impacts, Adaptation, and Vuln |
Issue |
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Pages |
1-32 |
| Keywords |
CropM |
| Abstract |
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| Address |
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| Corporate Author |
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Thesis |
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| Publisher |
Cambridge University Press |
Place of Publication |
Cambridge, United Kingdom and New York, NY, USA |
Editor |
Field, C.B.; Barros, V.R.; Dokken, D.J.; Mach, K.J.; Mastrandrea, M.D.; Bilir, T.E.; Chatterjee, M.; Ebi, K.L.; Estrada, Y.O.; Genova, R.C.; Girma, B.; Kissel, E.S.; Levy, A.N.; MacCracken, S.; Mastrandrea, P.R.; White, L.L. |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2500 |
| Permanent link to this record |
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| Author |
Dáder, B.; Fereres, A.; Trebicki, P. |
| Title |
Studying Myzus persicae performance and feeding behaviour, and associated plant viruses under increasing CO2 |
Type |
Conference Article |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
CropM |
| Abstract |
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| Address |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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ISBN |
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Expedition |
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Conference |
Annual Conference of the Australian Entomological Society. Canberra, Australia., 2014-09-28 to 2014-10-01 |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2378 |
| Permanent link to this record |
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| Author |
Hidy, D.; Balogh, J.; Churkina, G.; Haszpra, L.; Horváth, F.; Ittzés, P.; Ittzés, D.; Ma, S.; Nagy, Z.; Pintér, K.; Barcza, Z. |
| Title |
Structural development and web service based sensitivity analysis of the Biome-BGC MuSo model |
Type |
Conference Article |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
LiveM |
| Abstract |
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| Address |
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Thesis |
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Place of Publication |
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Editor |
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| Language |
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Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Issue |
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Edition |
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Expedition |
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Conference |
European GeoSciences Union (EGU), General Assembly 2014, 2014-04-28 to 2014-05-02 |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
2475 |
| Permanent link to this record |
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| Author |
Sharif, B.; Olesen, J.E.; Schelde, K. |
| Title |
Statistical learning approach for modelling the effects of climate change on oilseed rape yield |
Type |
Conference Article |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
Statistical learning is a fairly new term referring to a set of supervised and unsupervised modelling and prediction techniques. It is based on traditional statistics but has been highly enhanced inspired by developments in machine learning and data mining. The main focus of statistical learning is to estimate the functions that quantify relations between several parameters and observed responses. These functions are further used for prediction, inference or a combination of both. For a particular case of quantitative responses, regularization techniques in regression are developed to overcome the weaknesses of ordinary least square (OLS) regression in prediction. These new shrinkage methods outperform OLS for prediction, especially in large datasets. In this study, a large dataset of field experiments on winter oilseed rape in Denmark for 22 years (1992 to 2013) was collected. Biweekly climatic data along with sowing date, harvest date, soil type and previous crop are considered as the explanatory variables. Yield of winter oilseed rape is considered as response variable. LASSO and Elastic Nets are the regularization techniques used to estimate the functions. Hold-one-out cross validation method for testing the prediction power reveals that these techniques are much useful in both prediction and inference. Since these techniques are included in recent versions of some software packages (e.g. R), they can be easily implemented by users at any level. The estimated function (model) is further used to predict the oilseed rape yield responses to climate change for several scenarios using representative weather data produced by a weather generator. |
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Place of Publication |
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Editor |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
FACCE MACSUR Mid-term Scientific Conference |
| Series Volume |
3(S) Sassari, Italy |
Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
FACCE MACSUR Mid-term Scientific Conference, 2014-04-01 to 2014-04-04, Sassari, Italy |
| Notes |
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Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5129 |
| Permanent link to this record |
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| Author |
Nikolic, U. |
| Title |
Stand und Perspektiven des Sojaanbaues in Serbien – Untersuchung auf Gemeindeebene |
Type |
Book Whole |
| Year |
2014 |
Publication |
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Abbreviated Journal |
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| Volume |
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Issue |
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Pages |
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| Keywords |
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| Abstract |
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| Address |
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| Corporate Author |
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Thesis |
Master's thesis |
| Publisher |
Universität für Bodenkultur Wien |
Place of Publication |
Vienna |
Editor |
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| Language |
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Summary Language |
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Original Title |
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| Series Editor |
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Series Title |
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Abbreviated Series Title |
M.Sc. |
| Series Volume |
M.Sc. |
Series Issue |
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Edition |
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| ISSN |
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ISBN |
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Medium |
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| Area |
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Expedition |
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Conference |
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| Notes |
TradeM |
Approved |
no |
| Call Number |
MA @ admin @ |
Serial |
5153 |
| Permanent link to this record |
