Generalizations of Weighted Means and OWA Operators by Using Unimodal Weighting Vectors
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DOI: 10.1109/tfuzz.2019.2928513
Abstract: Weighted means and ordered weighted averaging (OWA) operators are two families of functions well known in the literature. Given that both are specific cases of the Choquet integral, several procedures for constructing capacities that generalize… read more here.
Keywords: owa operators; means owa; using unimodal; operators using ... See more keywords
On Kedlaya-type inequalities for weighted means
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DOI: 10.1186/s13660-018-1685-z
Abstract: AbstractIn 2016 we proved that for every symmetric, repetition invariant and Jensen concave mean M$\mathscr{M}$ the Kedlaya-type inequality A(x1,M(x1,x2),…,M(x1,…,xn))≤M(x1,A(x1,x2),…,A(x1,…,xn))$$ \mathscr{A} \bigl(x_{1},\mathscr{M}(x_{1},x_{2}), \ldots,\mathscr{M}(x _{1},\ldots,x_{n}) \bigr) \le \mathscr{M} \bigl( x_{1}, \mathscr{A}(x _{1},x_{2}), \ldots,\mathscr{A}(x_{1},\ldots,x_{n}) \bigr) $$ holds for… read more here.
Keywords: kedlaya type; weighted means; inequalities weighted; mathscr ldots ... See more keywords
On a new weighted Hermite-Hadamard inequality, application for weighted means
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DOI: 10.2298/fil2416895r
Abstract: The purpose of this paper is to introduce a weighted Hermite-Hadamard inequality which generalizes the standard one. Some refinements and reverses of this weighted inequality are pointed out. As application, some new weighted means are… read more here.
Keywords: hadamard inequality; inequality; weighted means; new weighted ... See more keywords
Bi-Partitioned Feature-Weighted K-Means Clustering for Detecting Insurance Fraud Claim Patterns
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DOI: 10.3390/math13030434
Abstract: The weighted K-means clustering algorithm is widely recognized for its ability to assign varying importance to features in clustering tasks. This paper introduces an enhanced version of the algorithm, incorporating a bi-partitioning strategy to segregate… read more here.
Keywords: means clustering; fraud; weighted means; claim ... See more keywords