Bressan, Glaucia M.Oliveira, Vilma A.Boaventura, Maurilio [UNESP]2014-05-272014-05-272009-12-01Proceedings of the IEEE International Conference on Control Applications, p. 1798-1803.http://hdl.handle.net/11449/71282This paper proposes a fuzzy classification system for the risk of infestation by weeds in agricultural zones considering the variability of weeds. The inputs of the system are features of the infestation extracted from estimated maps by kriging for the weed seed production and weed coverage, and from the competitiveness, inferred from narrow and broad-leaved weeds. Furthermore, a Bayesian network classifier is used to extract rules from data which are compared to the fuzzy rule set obtained on the base of specialist knowledge. Results for the risk inference in a maize crop field are presented and evaluated by the estimated yield loss. © 2009 IEEE.1798-1803engAgricultural zonesBayesian network classifiersClassification rulesCrop fieldsFuzzy classification systemsFuzzy rule setKrigingRisk predictionsWeed infestationWeed seedYield lossBayesian networksCompetitionInference enginesRisk perceptionTrabalho apresentado em evento10.1109/CCA.2009.5280694Acesso aberto2-s2.0-740491001806958497786939585