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| Registros recuperados : 11 | |
| 1. |  | NÖLSCHER, A. C.; YAÑEZ-SERRANO, A. M.; WOLFF, S.; ARAUJO, A. C. de; LAVRIC, J. V.; KESSELMEIER, J.; WILLIAMS, J. Unexpected seasonality in quantity and composition of Amazon rainforest air reactivity. Nature Communications, v. 7, art. n. 10383, 22 Jan. 2016.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 2. | | PFANNERSTILL, E. Y.; REIJRINK, N. G.; EDTBAUER, A.; RINGSDORF, A.; ZANNONI, N.; ARAUJO, A. C. de; DITAS, F.; HOLANDA, B. A.; SÁ, M. O.; TSOKANKUNKU, A.; WALTER, D.; WOLFF, S.; LAVRIC, J. V.; PÖHLKER, C.; SÖRGEL, M.; WILLIAMS, J. Total OH reactivity over the Amazon rainforest: variability with temperature, wind, rain, altitude, time of day, season, and an overall budget closure. Atmospheric Chemistry and Physics, v. 21, n. 8, p. 6231-6256, 2021.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 3. | | KOMIYA, S.; ARAUJO, A. C. de; LAVRIC, J. V.; NELSON, B.; SÖRGEL, M.; WEBER, B.; BOTIA, S.; GOMES-ALVES, E.; WALTER, D.; SÁ, M. de O.; WOLFF, S.; PINHO, D. M.; KONDO, F.; TRUMBORE, S. Seasonal and interannual variations of carbon fluxes at the Amazon Tall Tower Observatory site in 2014-2019. In: EGU GENERAL ASSEMBLY, 2022, Viena. Programme. [S.l.]: EGU, 2022.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 4. | | CORRÊA, P. B.; DIAS-JÚNIOR, C. Q.; CAVA, D.; SÖRGEL, M.; BOTÍA, S.; ACEVEDO, O.; OLIVEIRA, P. E. S.; MANZI, A. O.; MACHADO, L. A. T.; MARTINS, H. dos S.; TSOKANKUNKU, A.; ARAUJO, A. C. de; LAVRIC, J. V.; WALTER, D.; MORTARINI, L. A case study of a gravity wave induced by Amazon forest orography and low level jet generation. Agricultural and Forest Meteorology, v. 307, Article 108457, 2021.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 5. | | PFANNERSTILL, E. Y.; NÖLSCHER, A. C.; YÁÑEZ-SERRANO, A. M.; BOURTSOUKIDIS, E.; KEBEL, S.; JANSSEN, R. H. H.; TSOKANKUNKU, A.; WOLFF, S.; SÖRGEL, M.; SÁ, M. O.; ARAUJO, A. C. de; WALTER, D.; LAVRIC, J.; DIAS-JUNIOR, C. Q.; KESSELMEIER, J.; WILLIAMS, J. Total OH reactivity changes over the Amazon rainforest during an El Niño event. Frontiers in Forests and Global Change, v. 1, Article 12, Dec. 2018.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 6. | | ASPEREN, H. V.; WARNEKE, T.; ARAUJO, A. C. de; FORSBERG, B.; FERREIRA, S.; ALVES-OLIVEIRA, J.; OLIVEIRA, L. R. de; XAVIER, T. de L.; SÁ, M.; TEIXEIRA, P.; PIRES, E.; MOURA, V.; KOMIYA, S.; BOTIA, S.; JONES, S.; LAVRIČ, J.; TRUMBORE, S.; NOTHOLT, J. Tropical forest CH4 budget: the importance of local hotspots In: EGU GENERAL ASSEMBLY, 2022, Viena. Programme. [S.l.]: EGU, 2022.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 7. | | PÖHLKER, M. L.; PÖHLKER, C.; DITAS, F.; KLIMACH, T.; ANGELIS, I. H. de; ARAUJO, A. C. de; BRITO, J.; CARBONE, S.; CHENG, Y.; CHI, X.; DITZ, R.; GUNTHE, S. S.; KESSELMEIER, J.; KÖNEMANN, T.; LAVRIC, J. V.; MARTIN, S. T.; MIKHAILOV, E.; MORAN-ZULOAGA, D.; ROSE, D.; SATURNO, J.; SU, H.; THALMAN, R.; WALTER, D.; WANG, J.; WOLFF, S.; BARBOSA, H. M. J.; ARTAXO, P.; ANDREAE, M. O.; PÖSCHL, U. Long-term observations of cloud condensation nuclei in the Amazon rain forest - Part 1: Aerosol size distribution, hygroscopicity, and new model parametrizations for CCN prediction. Atmospheric Chemistry and Physics, v. 16, n. 24, p. 15709-15740, Dec. 2016. Na publicação: Araújo, A.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 8. | | PÖHLKER, M. L.; DITAS, F.; SATURNO, J.; KLIMACH, T.; ANGELIS, I. H. de; ARAUJO, A. C. de; BRITO, J.; CARBONE, S.; CHENG, Y.; CHI, X.; DITZ, R.; GUNTHE, S. S.; HOLANDA, B. A.; KANDLER, K.; KESSELMEIER, J.; KÖNEMANN, T.; KRÜGER, O. O.; LAVRIC, J. V.; MARTINS, S. T.; MIKHAILOV, E.; MORAN-ZULOAGA, D.; RIZZO, L. V.; ROSE, D.; SU, H.; THALMAN, R.; WALTER, D.; WANG, J.; WOLFF, S.; BARBOSA, H. M. J.; ARTAXO, P.; ANDREAE, M. O.; PÖSCHL, U.; PÖHLKER, C. Long-term observations of cloud condensation nuclei over the Amazon rain forest - Part 2: Variability and characteristics of biomass burning, long-range transport, and pristine rain forest aerosols. Atmospheric Chemistry and Physics, v. 18, n. 14, p. 10289-10331, 2018.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 9. | | ANDREAE, M. O.; ACEVEDO, O. C.; ARAUJO, A.; ARTAXO, P.; BARBOSA, C. G. G.; BARBOSA, H. M. J.; BRITO, J.; CARBONE, S.; CHI, X.; CINTRA, B. B. L.; SILVA, N. F. da; DIAS, N. L.; DIAS-JÚNIOR, C. Q.; DITAS, F.; DITZ, R.; GODOI, A. F. L.; GODOI, R. H. M.; HEIMANN, M.; HOFFMANN, T.; KESSELMEIER, J.; KÖNEMANN, T.; KRÜGER, M. L.; LAVRIC, J. V.; MANZI, A. O.; MORAN-ZULOAGA, D.; NÖLSCHER, A. C.; NOGUEIRA, D. S.; PIEDADE, M. T. F.; PÖHLKER, C.; PÖSCHL, U.; RIZZO, L. V.; RO, C.-U.; RUCKTESCHLER, N.; SÁ, L. D. A.; SÁ, M. D. O.; SALES, C. B.; SANTOS, R. M. N. dos; SATURNO, J.; SCHÖNGART, J.; SÖRGEL, M.; SOUZA, C. M. de; SOUZA, R. A. F. de; SU, H.; TARGHETTA, N.; TÓTA, J.; TREBS, I.; TRUMBORE, S.; EIJCK, A. van; WALTER, D.; WANG, Z.; WEBER, B.; WILLIAMS, J.; WINDERLICH, J.; WITTMANN, F.; WOLFF, S.; YÁÑEZ-SERRANO, A. M. The Amazon Tall Tower Observatory (ATTO) in the remote Amazon basin: overview of first results from ecosystem ecology, meteorology, trace gas, and aerosol measurements. Atmospheric Chemistry and Physics Discuss, v. 15, n. 18, p. 11599-11726, 2015.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 10. | | WENDISCH, M.; PÖSCHL, U.; ANDREAE, M. O.; MACHADO, L. A. T.; ALBRECHT, R.; SCHLAGER, H.; ROSENFELD, D.; MARTIN, S. T.; ABDELMONEM, A.; AFCHINE, A.; ARAUJO, A. C.; ARTAXO, P.; AUFMHOFF, H.; BARBOSA, H. M. J.; BORRMANN, S.; BRAGA, R.; BUCHHOLZ, B.; CECCHINI, M. A.; COSTA, A.; CURTIUS, J.; DOLLNER, M.; DORF, M.; DREILING, V.; EBERT, V.; EHRLICH, A.; EWALD, F.; FISCH, G.; FIX, A.; FRANK, F.; FÜTTERER, D.; HECKL, C.; HEIDELBERG, F.; HÜNEKE, T.; JÄKEL, E.; JÄRVINEN, E.; JURKAT, T.; KANTER, S.; KÄSTNER, U.; KENNTNER, M.; KESSEKMEIER, J.; KLIMACH, T.; KNECHT, M.; KOHL, R.; KÖLLING, T.; KRÄMER, M.; KRÜGER, M.; KRISNA, T. C.; LAVRIC, J. V.; LONGO, K.; MAHNKE, C.; MANZI, A. O.; MAYER, B.; MERTES, S.; MINIKIN, A.; MOLLEKER, S.; MÜNCH, S.; NILIUS, B.; PFEILSTICKER, K.; PÖHLKER, C.; ROIGER, A.; ROSE, D.; ROSENOW, D.; SAUER, D.; SCHNAITER, M.; SCHNEIDER, J.; SCHULZ, C.; SOUZA, R. A. F. de; SPANU, A.; STOCK, P.; VILA, D.; VOIGT, C.; WALSER, A.; WALTER, D.; WEIGEL, R.; WEINZIERL, B.; WERNER, F.; YAMASOE, M. A.; ZIEREIS, H.; ZINNER, T.; ZÖGER, M. Acridicon-Chuva campaign: studying tropical deep convective clouds and precipitation over Amazonia using the New German research aircraft HALO. Bulletin of the American Meteorological Society, v. 97, n. 10, p. 1885-1908, Oct. 2016.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| 11. | | ANDREAE, M. O.; ACEVEDO, O. C.; ARAUJO, A.; ARTAXO, P.; BARBOSA, C. G. G.; BARBOSA, H. M. J.; BRITO, J.; CARBONE, S.; CHI, X.; CINTRA, B. B. L.; SILVA, N. F. da; DIAS, N. L.; DIAS-JÚNIOR, C. Q.; DITAS, F.; DITZ, R.; GODOI, A. F. L.; GODOI, R. H. M.; HEIMANN, M.; HOFFMANN, T.; KESSELMEIER, J.; KÖNEMANN, T.; KRÜGER, M. L.; LAVRIC, J. V.; MANZI, A. O.; LOPES, A. P.; MARTINS, D. L.; MIKHAILOV, E. F.; MORAN-ZULOAGA, D.; NELSON, B. W.; NÖLSCHER, A. C.; NOGUEIRA, D. S.; PIEDADE, M. T. F.; PÖHLKER, C.; PÖSCHL, U.; QUESADA, C. A.; RIZZO, L. V.; RO, C.-U.; RUCKTESCHLER, N.; SÁ, L. D. A.; SÁ, M. de O.; SALES, C. B.; SANTOS, R. M. N. dos; SATURNO, J.; SCHÖNGART, J.; SÖRGEL, M.; SOUZA, C. M. de; SOUZA, R. A. F. de; SU, H.; TARGHETTA, N.; TÓTA, J.; TREBS, I.; TRUMBORE, S.; EIJCK, A. van; WALTER, D.; WANG, Z.; WEBER, B.; WILLIAMS, J.; WINDERLICH, J.; WITTMANN, F.; WOLFF, S.; YÁÑEZ-SERRANO, A. M. The Amazon Tall Tower Observatory (ATTO): overview of pilot measurements on ecosystem ecology, meteorology, trace gases, and aerosols. Atmospheric Chemistry and Physics, v. 15, n. 18, p. 10723-10776, 2015.| Biblioteca(s): Embrapa Amazônia Oriental. |
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| Registros recuperados : 11 | |
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Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
02/01/2019 |
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Data da última atualização: |
21/01/2020 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
RODRIGUES, L. S.; REZENDE, S. O.; MOURA, M. F.; MARCACINI, R. M. |
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Afiliação: |
LUCAS S. RODRIGUES, UFMS; SOLANGE O. REZENDE, UFSCar; MARIA FERNANDA MOURA, CNPTIA; RICARDO M. MARCACINI, UFMS. |
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Título: |
Agribusiness time series forecasting using perceptually important events. |
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Ano de publicação: |
2018 |
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Fonte/Imprenta: |
In: LATIN AMERICAN COMPUTING CONFERENCE, 44., 2018, São Paulo. Anais... São Paulo: Mackenzie, 2018. |
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Páginas: |
10 p. |
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Idioma: |
Inglês |
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Notas: |
CLEI 2018. |
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Conteúdo: |
Resumo- Modern agribusiness management incorporates instruments for risk management with the objective of mitigating uncertainties to the producer. In this context, the producer (riskaverse) transfer the risk of price oscillation to companies or individuals that operate in the futures market and who expect to receive a payment (risk premium) for assuming such risk. Defining the adequate strategies for risk management depends on the knowledge about the problem to determine prices ranges in the future. Recent studies demonstrate that time series forecasting can be significantly improved by considering additional inforation about the problem. In particular, besides the historical time series, textual knowledge extracted from the news portals, social networking and other public data sources available in the web may also be used. This paper presents an approach for agribusiness time series forecasting that allows incorporating external knowledge in the form of events extracted from news about agribusiness, without the need to previously label textual information. In this case, periods of significant uptrends and downtrends of time series are automatically identified - known in the literature as perceptually important points (PIP). We extend the concept of PIP to news events, where similar events published with a certain regularity in periods of uptrends and owntrends are selected as perceptually important events to improve time series forecasting models. An experimental evaluation based on price prediction on ten corn futures contracts (derivatives) provides evidence that the proposed approach is promising. MenosResumo- Modern agribusiness management incorporates instruments for risk management with the objective of mitigating uncertainties to the producer. In this context, the producer (riskaverse) transfer the risk of price oscillation to companies or individuals that operate in the futures market and who expect to receive a payment (risk premium) for assuming such risk. Defining the adequate strategies for risk management depends on the knowledge about the problem to determine prices ranges in the future. Recent studies demonstrate that time series forecasting can be significantly improved by considering additional inforation about the problem. In particular, besides the historical time series, textual knowledge extracted from the news portals, social networking and other public data sources available in the web may also be used. This paper presents an approach for agribusiness time series forecasting that allows incorporating external knowledge in the form of events extracted from news about agribusiness, without the need to previously label textual information. In this case, periods of significant uptrends and downtrends of time series are automatically identified - known in the literature as perceptually important points (PIP). We extend the concept of PIP to news events, where similar events published with a certain regularity in periods of uptrends and owntrends are selected as perceptually important events to improve time series forecasting models. An experimental evaluatio... Mostrar Tudo |
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Palavras-Chave: |
Séries temporais. |
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Thesagro: |
Agronegócio. |
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Thesaurus NAL: |
Agribusiness; Risk management. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/189590/1/agribusiness-time.pdf
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Marc: |
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100 1 $aRODRIGUES, L. S.
245 $aAgribusiness time series forecasting using perceptually important events.$h[electronic resource]
260 $aIn: LATIN AMERICAN COMPUTING CONFERENCE, 44., 2018, São Paulo. Anais... São Paulo: Mackenzie$c2018
300 $a10 p.
500 $aCLEI 2018.
520 $aResumo- Modern agribusiness management incorporates instruments for risk management with the objective of mitigating uncertainties to the producer. In this context, the producer (riskaverse) transfer the risk of price oscillation to companies or individuals that operate in the futures market and who expect to receive a payment (risk premium) for assuming such risk. Defining the adequate strategies for risk management depends on the knowledge about the problem to determine prices ranges in the future. Recent studies demonstrate that time series forecasting can be significantly improved by considering additional inforation about the problem. In particular, besides the historical time series, textual knowledge extracted from the news portals, social networking and other public data sources available in the web may also be used. This paper presents an approach for agribusiness time series forecasting that allows incorporating external knowledge in the form of events extracted from news about agribusiness, without the need to previously label textual information. In this case, periods of significant uptrends and downtrends of time series are automatically identified - known in the literature as perceptually important points (PIP). We extend the concept of PIP to news events, where similar events published with a certain regularity in periods of uptrends and owntrends are selected as perceptually important events to improve time series forecasting models. An experimental evaluation based on price prediction on ten corn futures contracts (derivatives) provides evidence that the proposed approach is promising.
650 $aAgribusiness
650 $aRisk management
650 $aAgronegócio
653 $aSéries temporais
700 1 $aREZENDE, S. O.
700 1 $aMOURA, M. F.
700 1 $aMARCACINI, R. M.
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Embrapa Agricultura Digital (CNPTIA) |
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