Ejemplo n.º 1
0
        internal void IsConvex_WhenPointsAllDecreasing_ReturnsTrue()
        {
            // Arrange
            var function = TrapezoidalFunction.CreateWithLeftEdge(0, 3);
            var fuzzySet = new FuzzySet("some_fuzzy_state", function);

            // Act
            var result = fuzzySet.IsConvex;

            // Assert
            Assert.True(result);
        }
Ejemplo n.º 2
0
 /// <summary>
 /// Returns a <see cref="LinguisticVariable"/> representing fan speed.
 /// </summary>
 /// <returns>
 /// The <see cref="LinguisticVariable"/>.
 /// </returns>
 public static LinguisticVariable PumpSpeed()
 {
     return(new LinguisticVariable(
                InputVariable.PumpSpeed,
                new List <FuzzySet>
     {
         new FuzzySet(TestKit.PumpSpeed.Off, SingletonFunction.Create(0)),
         new FuzzySet(TestKit.PumpSpeed.VeryLow, TrapezoidalFunction.CreateWithLeftEdge(1, 200)),
         new FuzzySet(TestKit.PumpSpeed.Low, TriangularFunction.Create(0, 500, 1000)),
         new FuzzySet(TestKit.PumpSpeed.Moderate, TriangularFunction.Create(500, 1000, 2000)),
         new FuzzySet(TestKit.PumpSpeed.High, TriangularFunction.Create(3000, 3500, 4000)),
         new FuzzySet(TestKit.PumpSpeed.VeryHigh, TrapezoidalFunction.CreateWithRightEdge(3500, 4999)),
         new FuzzySet(TestKit.PumpSpeed.AtLimit, SingletonFunction.Create(5000))
     }));
 }
        internal void CreateWithLeftEdge_GetMembershipWithVariousInputs_ReturnsExpectedResult(
            double x1,
            double x2,
            double input,
            double expected)
        {
            // Arrange
            var function = TrapezoidalFunction.CreateWithLeftEdge(x1, x2);

            // Act
            var result = function.GetMembership(input);

            // Assert
            Assert.Equal(UnitInterval.Create(expected), result);
        }
Ejemplo n.º 4
0
        internal void RunMamdaniInference(double foodInput, double serviceInput, double expected)
        {
            // Define the input and output linguistic variables.
            var foodQuality = new LinguisticVariable(
                InputVariable.FoodQuality,
                new List <FuzzySet>
            {
                new FuzzySet(FoodQuality.Poor, TrapezoidalFunction.CreateWithLeftEdge(0, 5)),
                new FuzzySet(FoodQuality.Average, TriangularFunction.Create(0, 5, 10)),
                new FuzzySet(FoodQuality.Good, TrapezoidalFunction.CreateWithRightEdge(5, 10))
            });

            var serviceQuality = new LinguisticVariable(
                InputVariable.FoodQuality,
                new List <FuzzySet>
            {
                new FuzzySet(ServiceQuality.Poor, TrapezoidalFunction.CreateWithLeftEdge(0, 5)),
                new FuzzySet(ServiceQuality.Average, TriangularFunction.Create(0, 5, 10)),
                new FuzzySet(ServiceQuality.Good, TrapezoidalFunction.CreateWithRightEdge(5, 10))
            });

            var tipAmount = new LinguisticVariable(
                OutputVariable.TipAmount,
                new List <FuzzySet>
            {
                new FuzzySet(TipAmount.Low, TrapezoidalFunction.CreateWithLeftEdge(0, 13)),
                new FuzzySet(TipAmount.Medium, TriangularFunction.Create(0, 13, 25)),
                new FuzzySet(TipAmount.High, TrapezoidalFunction.CreateWithRightEdge(13, 25))
            });

            // Define the rules for the fuzzy inference engine.
            var rule1 = new FuzzyRuleBuilder(TippingProblem.Rule1)
                        .If(foodQuality.Is(FoodQuality.Poor))
                        .Or(serviceQuality.Is(ServiceQuality.Poor))
                        .Then(tipAmount.Is(TipAmount.Low))
                        .Build();

            var rule2 = new FuzzyRuleBuilder(TippingProblem.Rule2)
                        .If(serviceQuality.Is(ServiceQuality.Average))
                        .Then(tipAmount.Is(TipAmount.Medium))
                        .Build();

            var rule3 = new FuzzyRuleBuilder(TippingProblem.Rule3)
                        .If(foodQuality.Is(FoodQuality.Good))
                        .Or(serviceQuality.Is(ServiceQuality.Good))
                        .Then(tipAmount.Is(TipAmount.High))
                        .Build();

            // Construct the fuzzy inference engine.
            var tnorm       = TriangularNormFactory.MinimumTNorm();
            var tconorm     = TriangularConormFactory.MaximumTConorm();
            var defuzzifier = new CentroidDefuzzifier();
            var fuzzyEngine = new MamdaniInferenceEngine(tnorm, tconorm, defuzzifier);

            // Add the rules to the rulebase.
            fuzzyEngine.Rulebase.AddRule(rule1);
            fuzzyEngine.Rulebase.AddRule(rule2);
            fuzzyEngine.Rulebase.AddRule(rule3);

            // Prepare database to receive inputs.
            fuzzyEngine.Database.AddVariable(Label.Create(InputVariable.FoodQuality));
            fuzzyEngine.Database.AddVariable(Label.Create(InputVariable.ServiceQuality));

            // Generate input data.
            var foodData    = new DataPoint(InputVariable.FoodQuality, foodInput);
            var serviceData = new DataPoint(InputVariable.ServiceQuality, serviceInput);

            // Feed inference engine the data.
            fuzzyEngine.Database.UpdateData(foodData);
            fuzzyEngine.Database.UpdateData(serviceData);

            // Compute the inference engine.
            var result = fuzzyEngine.Compute();

            Assert.Equal(OutputVariable.TipAmount.ToString(), result[0].Subject.Value);
            Assert.Equal(expected, result[0].Value);
        }