List of available XMCDA web services

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A C D E F G I L M N O P R S T U W X

defuzzificationCOG Version: 1.0 Provider: URV

Description: Implementation of a defuzzification of set of fuzzy labels Java implementation of a defuzzification of set of fuzzy labels according to the COG method: Center of Gravity.


defuzzificationCOM Version: 1.0 Provider: URV

Description: Implementation of a defuzzification of set of fuzzy labels according to the COM method (Center of Maximum). The method consists in returning the point in the center of the interval where the membe ...


defuzzificationOrdinal Version: 1.0 Provider: URV

Description: Implementation of a defuzzification of set of fuzzy labels according to their position. The first label is assigned the position 0.0, the second the position 1.0, and so on. No interpretation base ...


fuzzyLabelsDescriptors Version: 1.0 Provider: URV

Description: Two types of uncertainty in fuzzy sets are recognized: (1) specificity, related to the measurement of imprecision, which is based on the cardinality of the set, and (2) fuzziness, or entropy, whic ...


OWA Version: 1.0 Provider: URV

Description: The Ordered Weighted Averaging operators, commonly called OWA operators, provide a parameterized class of mean type aggregation operators.


OWAWeightsBalance Version: 1.0 Provider: URV

Description: Balance of the weights given to the Ordered Weighted Average operator (OWA)


OWAWeightsDivergence Version: 1.0 Provider: URV

Description: Divergence of the weights given to the Ordered Weighted Average operator (OWA)


OWAWeightsEntropy Version: 1.0 Provider: URV

Description: Entropy of the weights given to the Ordered Weighted Average operator (OWA)


OWAWeightsOrness Version: 1.0 Provider: URV

Description: Orness of the weights given to the Ordered Weighted Average operator (OWA)


ULOWA Version: 1.1 Provider: URV

Description: This module implements the ULOWA aggregation operator: Unbalanced Linguistic Ordered Weighted Average. Aggregation operators for linguistic variables usually assume uniform and symmetrical distrib ...