Por favor, use este identificador para citar o enlazar este ítem:
http://www.alice.cnptia.embrapa.br/alice/handle/doc/1021081Registro completo de metadatos
| Campo DC | Valor | Lengua/Idioma |
|---|---|---|
| dc.contributor.author | MASSRUHA, S. M. F. S. | pt_BR |
| dc.contributor.author | SANDRI, S. | pt_BR |
| dc.contributor.author | WAINER, J. | pt_BR |
| dc.contributor.author | MORANDI, M. A. B. | pt_BR |
| dc.date.accessioned | 2015-07-31T11:11:11Z | pt_BR |
| dc.date.available | 2015-07-31T11:11:11Z | pt_BR |
| dc.date.created | 2015-07-31 | pt_BR |
| dc.date.issued | 2005 | pt_BR |
| dc.identifier.citation | In: CONFERENCE OF THE EUROPEAN FEDERATION FOR INFORMATION TECHNOLOGY IN AGRICULTURE, FOOD AND ENVIRONMENT, 5., WORLD CONGRESS ON COMPUTERS IN AGRICULTURE AND NATURAL RESOURCES, 3., 2005, Vila Real, Portugal. [Proceedings...] Vila Real, Portugal: EFITA/WCCA, 2005. p. 1400-1407. | pt_BR |
| dc.identifier.uri | http://www.alice.cnptia.embrapa.br/alice/handle/doc/1021081 | pt_BR |
| dc.description | The goal of this paper is to give an overview of a general problem-solving framework for diagnosis, investigation and treatment tasks, that incorporates concepts of abductive inference, fuzzy set logic and decision theory. In this work we focus on the use of this framework in agriculture, with an illustration in corn plantations. The general framework models time durations and intensity of manifestations as fuzzy sets, and, in the particular case of agriculture, it takes into account the favorable conditions for the development of a given disorder and the severity of its manifestations to recommend a treatment, together with other important factors such as risk and cost. | pt_BR |
| dc.language.iso | eng | eng |
| dc.rights | openAccess | eng |
| dc.subject | Abductive inference | pt_BR |
| dc.subject | Fuzzy sets | pt_BR |
| dc.title | An integrated framework for clinical problem solving in agriculture. | pt_BR |
| dc.type | Artigo em anais e proceedings | pt_BR |
| dc.date.updated | 2015-08-19T11:11:11Z | pt_BR |
| dc.subject.thesagro | Diagnóstico | pt_BR |
| riaa.ainfo.id | 1021081 | pt_BR |
| riaa.ainfo.lastupdate | 2015-08-19 | pt_BR |
| dc.contributor.institution | SÍLVIA MARIA FONSECA SILVEIRA MASSRUHÁ, CNPTIA; SANDRA SANDRI, Institut d'investigació en Intelligencia Artificial - IIIA/CSIC, Belaterra, Spain; JACQUES WAINER, IC/Unicamp; MARCELO AUGUSTO BOECHAT MORANDI, CNPMA. | pt_BR |
| Aparece en las colecciones: | Artigo em anais de congresso (CNPMA)  | |
Ficheros en este ítem:
| Fichero | Descripción | Tamaño | Formato | |
|---|---|---|---|---|
| 2005AA086.pdf | 2.2 MB | Adobe PDF |  Visualizar/Abrir |
