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+/*
+ fuzzylite (R), a fuzzy logic control library in C++.
+ Copyright (C) 2010-2017 FuzzyLite Limited. All rights reserved.
+ Author: Juan Rada-Vilela, Ph.D. <jcrada@fuzzylite.com>
+
+ This file is part of fuzzylite.
+
+ fuzzylite is free software: you can redistribute it and/or modify it under
+ the terms of the FuzzyLite License included with the software.
+
+ You should have received a copy of the FuzzyLite License along with
+ fuzzylite. If not, see <http://www.fuzzylite.com/license/>.
+
+ fuzzylite is a registered trademark of FuzzyLite Limited.
+ */
+
+#ifndef FL_WEIGHTEDAVERAGECUSTOM_H
+#define FL_WEIGHTEDAVERAGECUSTOM_H
+
+#include "fl/defuzzifier/WeightedDefuzzifier.h"
+
+namespace fl {
+    class Activated;
+
+    /**
+      The (experimental) WeightedAverageCustom class is a WeightedDefuzzifier that computes the
+      weighted average of a fuzzy set represented in an Aggregated Term utilizing
+      the fuzzy operators for implication and aggregation to compute the weighted
+      average.  This is an experimental approach to take advantage of customization
+      thanks to the object-oriented design.
+
+      @author Juan Rada-Vilela, Ph.D.
+      @see WeightedAverage
+      @see WeightedSum
+      @see WeightedSumCustom
+      @see WeightedDefuzzifier
+      @see Defuzzifier
+      @since 6.0
+     */
+    class FL_API WeightedAverageCustom : public WeightedDefuzzifier {
+    public:
+        explicit WeightedAverageCustom(Type type = Automatic);
+        explicit WeightedAverageCustom(const std::string& type);
+        virtual ~WeightedAverageCustom() FL_IOVERRIDE;
+        FL_DEFAULT_COPY_AND_MOVE(WeightedAverageCustom)
+
+        virtual std::string className() const FL_IOVERRIDE;
+
+        virtual Complexity complexity(const Term* term) const FL_IOVERRIDE;
+
+        /**
+          Computes the weighted average of the given fuzzy set represented as
+          an AggregatedTerm as @f$y = \dfrac{\sum_i w_iz_i}{\sum_i w_i} @f$,
+          where @f$w_i@f$ is the activation degree of term @f$i@f$, and
+          @f$z_i = \mu_i(w_i) @f$.
+
+          If the implication and aggregation operators are set to fl::null (or
+          set to AlgebraicProduct and UnboundedSum, respectively), then the
+          operation of WeightedAverageCustom is the same as the WeightedAverage.
+          Otherwise, the implication and aggregation operators are utilized to
+          compute the multiplications and sums in @f$y@f$, respectively.
+
+          @param term is the fuzzy set represented as an Aggregated Term
+          @param minimum is the minimum value of the range (only used for Tsukamoto)
+          @param maximum is the maximum value of the range (only used for Tsukamoto)
+          @return the weighted average of the given fuzzy set
+         */
+        virtual scalar defuzzify(const Term* term,
+                scalar minimum, scalar maximum) const FL_IOVERRIDE;
+        virtual WeightedAverageCustom* clone() const FL_IOVERRIDE;
+
+        static Defuzzifier* constructor();
+    };
+}
+
+#endif  /* FL_WEIGHTEDAVERAGECUSTOM_H */
+