Weighted means
Constructing Choquet integral based operators that generalize weighted means and OWA operators
... fields. Weighted means and ordered weighted averaging (OWA) operators (introduced by Yager [1]) are well-known functions widely used for this ...by means of weighting vectors, but their ...
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Generalizations of weighted means and OWA operators by using unimodal weighting vectors
... Abstract—Weighted means and OWA operators are two fam- ilies of functions well known in the ...the weighted means and the OWA operators have been suggested in recent ...
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An analysis of Winsorized weighted means
... In this paper we have generalized Winsorized means to include weighting vec- tors. For this, we have introduced, in a natural way, a new family of functions called Winsorized weighted means. These ...
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An analysis of some functions that generalizes weighted means and OWA operators
... In this paper we have analyzed several functions proposed in the literature to simultaneously generalize weighted means and OWA operators. On the one hand, OWAWA operators do not generalize weighted ...
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SUOWA operators: An analysis of their conjunctive/disjunctive character
... (mainly weighted means and OWA operators) are a well-known family of functions widely used in several scientific ...generalize weighted means and OWA operators, and provide conditions under ...
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SUOWA operators: Constructing semi-uninorms And analyzing specific cases
... Given that semi-uninorms play a fundamental role in the definition of SUOWA operators, in this paper we show two procedures to construct semi-uninorms. The first one, based on the notion of ordinal sums of aggregation ...
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new class of functions for integrating weighting means and OWA operators
... of weighted means, OWA operators and Choquet ...by means of which we can integrate weighted means and OWA operators in a new class of operators, the SUOWA ...
10
On the relationship between the Crescent Method and SUOWA operators
... the weighted means and the ordered weighted averaging (OWA) operators ...combine weighted means and OWA ...the weighted ordered weighted averaging (WOWA) operators [3] and ...
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Structural and spectral properties of minimal strong digraphs
... The second meaningful difference between trees and MSDs is the complex- ity of the following algorithmic problem: Given a weighted connected graph and a weighted strong digraph, find the minimum spanning ...
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A-means: improving the cluster assignment phase of k-means for Big Data
... In the classification step of k-means, the membership of a data point to a cluster is determined based on the maximal closeness of the point to each of the centroids. The distance calculations are computationally ...
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Particle swarm optimization para problemas de secuenciamiento: total weighted tardiness
... En el problema de scheduling de Total Weighted Tardiness para máquina única [24], n jobs se procesan sin interrupción en una única máquina. Ésta sólo puede procesar un único job a la vez. Todo job j (j = 1, ...,n) ...
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Population and trends in the global mean temperature
... population- weighted temperature trend differs in key details from the area-weighted temperature trend; (2) that conflation is a bigger problem than non-representativeness; (3) that the urban heat island ...
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16639224
... where is a positive real number such that ϕ() > 0 (the existence of is guaranteed since we are assuming that ϕ ≡ 0), together with the characterization of the weighted weak type inequalities for M (see [5] and ...
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Fuzzy C Means : Distribuido en la nube
... Como el objetivo primario es la adaptación de un algoritmo comenzamos acercándonos paulatinamente a los conceptos necesarios para entender dicho algoritmo -Fuzzy C-Means- y su utilidad, estos conceptos son el Big ...
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ON ENTRE K MEANS Y REDES NEURONALES
... Dentro de los algoritmos de cluster lineales no supervisados nos centramos en el K-means (Hartigan & Wong 1979) de gran utilidad para los m´ etodos de clasificaci´ on, ya que, permite hacer particiones de ...
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A Comparison of Fuzzy Clustering Algorithms Applied to Feature Extraction on Vineyard
... Possibilistic C-Means Algorithm (PCM). The PCM algorithm considers the clustering problem from the viewpoint of possibility theory [10]. The ap- proach adopted in PCM differs from the FCM algorithm because the ...
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Consumer Processing of Online Trust Signals: A Neuroimaging Study
... outstanding means to objectively study the effectiveness of each e-Assurance as the comparison of brain activations elicited by seals of approval, rating systems or assurance statements during product evaluation ...
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03 Successful Home Canning
... with boiling water and bring to boil for 2 min. Fill jars loosely with hot peas and added cooking liquid, leaving 1-in. Weighted gauge- pints: 15 lbs. Weighted gauge- pints: 5 lbs.. V[r] ...
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TítuloNew Computation of Resolving Connected Dominating Sets in Weighted Networks
... A CDS is a subset of vertices constituting a connected induced subgraph such that every vertex in the network is either in the CDS or has a neighbor in it. The CDS with minimum cardinality or minimum CDS (MCDS) is a ...
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Classical operators on weighted Bergman and mixed norm spaces
... The theory of tent spaces introduced by Coifman, Meyer and Stein [17], and further studied by Cohn and Verbitsky [16] among others, shows the importance of maximal and square area functions and other objects from ...
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