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Fuzzy rule-based modelling has the potential to revolutionize many fields as it can handle uncertainty in modelling problems too complex to be approached by stochastic analysis.
Contents
IntroductionBasic Elements and DefinitionsFuzzy Sets: Definitions and PropertiesFuzzy NumbersAssessment of the Membership FunctionsFuzzy Sets, Possibilities and ProbabilitiesFuzzy RulesThe Structure of a Fuzzy RuleCombination of Fuzzy Rule ResponsesDefuzzificationCase of Fuzzy PremisesRules with Multiple ResponsesRule SystemsCompleteness and RedundancyVariables to Be Used for Rule SystemsRules and Continuous FunctionsMembership Functions in Rule SystemsSensitivity of the Response FunctionsRule ConstructionExplicit Rule SpecificationDeriving Rule Systems from DatasetsKnown Rule StructurePartially Explicit Rule StructuresUnknown Rule StructureDeriving Rule Systems from Fuzzy DataRule VerificationRemoving Unnecessary RulesFuzzy Rule-Based Modeling versus Fuzzy ControlPrinciples of Fuzzy ControlExamples of Fuzzy ControlFuzzy Control and Fuzzy Rule-Based ModelingRule Systems with Discrete ResponsesCombination of Discrete Consequence Type RulesRule AssessmentApplication to Weather ClassificationApplication to Time SeriesRule AssessmentExample: Water Demand ForecastingExample: Daily Mean TemperatureApplication to Dynamical Physical SystemsApplication to Soil Water MovementOther ApplicationsApplication to Medical DiagnosisSustainable Reservoir OperationReferencesA Proofs of Selected Propositions
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