AM - Artículos: Envíos recientes
Mostrando ítems 1-20 de 68
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Data-Driven Screening of Network Constraints for Unit Commitment
(IEEE Xplore, 2020)The transmission-constrained unit commitment (TC-UC) problem is one of the most relevant problems solved by independent system operators for the daily operation of power systems. Given its computational complexity, this ... -
Automatic feature scaling and selection for support vector machine classification with functional data.
(Springer Nature, 2020)Functional Data Analysis (FDA) has become a very important field in recent years due to its wide range of applications. However, there are several real-life applications in which hybrid functional data appear, i.e., data ... -
A novel embedded min-max approach for feature selection in nonlinear Support Vector Machine classification
(Elsevier, 2021)In recent years, feature selection has become a challenging problem in several machine learning fields, such as classification problems. Support Vector Machine (SVM) is a well-known technique applied in classification ... -
On the radicality property for spaces of symbols of bounded Volterra operators
(Elsevier, 2024-09)In [1] it is shown that the Bloch space in the unit disc has the following radicality property: if an analytic function g satisfies that , then , for all . Since coincides with the space of analytic symbols g such that the ... -
High-order in-cell discontinuous reconstruction path-conservative methods for nonconservative hyperbolic systems–DR.MOOD method
(Wiley, 2024)In this work, we develop a new framework to deal numerically with discontinuous solutions in nonconservative hyperbolic systems. First an extension of the MOOD methodology to nonconservative systems based on Taylor expansions ... -
Unifying Chance-Constrained and Robust Optimal Power Flow for Resilient Network Operations.
(IEEE, 2024)Uncertainty in renewable energy generation has the potential to adversely impact the operation of electric networks. Numerous approaches to manage this impact have been proposed, ranging from stochastic and chance-constrained ... -
Asymptotic properties of parameter estimates for random fields with tapered data.
(Institute of Mathematical Statistics, 2017)In this paper we present novel results on the asymptotic behavior of the so-called Ibragimov minimum contrast estimates. The case of tapered data for various models of Gaussian random fields is investigated. The CLT for ... -
Using Peer Review for Student Performance Enhancement: Experiences in a Multidisciplinary Higher Education Setting.
(MDPI, 2021-02)Nowadays one of the main focuses of the Spanish University system is achieving the active learning paradigm in the context of its integration into the European Higher Education Area. This goal is being addressed by means ... -
Log-Gaussian Cox Process in Infinite-Dimensional Spaces.
(American Mathematical Society, 2018)This paper introduces new results on doubly stochastic Poisson processes, with log-Gaussian Hilbert-valued random intensity (LGHRI), defined from the Ornstein-Uhlenbeck process (O-U process) in Hilbert spaces. Sufficient ... -
Words of analytic paraproducts on Hardy and weighted Bergman spaces.
(Elsevier, 2024)For a fixed analytic function g on the unit disc, we consider the analytic paraproducts induced by g, which are formally defined by , , and . We are concerned with the study of the boundedness of operators in the algebra ... -
Weighted inequalities for harmonic means.
(Ele-Math, 2006)We characterize the weighted weak and strong type (p, q) inequalities for the harmonic averaging operator Tf(x) = x/∫0x 1/f in the cases 0 < p ≤ q < ∞ and 0 < q < p < ∞. -
Weighted weak type inequalities for modified Hardy operators and geometric means operators in dimensions one and greater.
(Elsevier, 2007-03-12)We characterize the pairs of weights such that the geometric mean operator , defined for positive functions f on by verifies the weak type inequality in the case . Similar results are obtained for the n-dimensional ... -
Weighted modular inequalities for Hardy-Steklov operators.
(Elsevier, 2005-10-26)We characterize weighted modular inequalities of weak and strong type for the Hardy–Steklov operators T defined by , where g is a positive function and s, h are increasing and continuous functions such that for all x. -
Weighted inequalities for the one-sided geometric maximal operators.
(Wiley, 2011)We characterize the pairs of weights (u, v) such that the one-sided geometric maximal operator G+, defined for functions f of one real variable by G+ f(x) = sup h>0 exp 1 h x+h x log |f| , verifies the ... -
Weighted inequalities for Cesàro maximal operator in Orlicz spaces.
(Cambridge University Press, 2005-04-26)Let 0 < α ≤ 1 and let M+α be the Cesàro maximal operator of order α defined by In this work we characterize the pairs of measurable, positive and locally integrable functions (u, v) for which there exists a constant C > 0 ... -
Weighted bilinear Hardy inequalities.
(Elsevier, 2012)We characterize the weights w, w1, w2 such that the weighted bilinear Hardy inequality b a x a f q x a g q w(x)dx 1q C b a f p1w1 1 p1 b a gp2 w2 1 p2 holds for all nonnegative ... -
Hardy operators on weighted amalgams.
(Cambridge University Press, 2010-02-04)We characterize the boundedness of the Hardy operator between weighted amalgams, a problem studied, but not completely solved, by C. Carton-Lebrun, H. P. Heinig and S. C. Hofmann. We also characterize the weighted weak-type ... -
Some new weighted weak-type iterated and bilinear modified Hardy inequalities
(Springer Nature, 2024-03-02)We characterize the good weights for some weighted weak-type iterated and bilinear modified Hardy inequalities to hold. -
Point pattern analysis and classification on compact two-point homogeneous spaces evolving time.
(2023-02-14)This paper introduces a new modeling framework for the statistical analysis of point patterns on a manifold Md; defined by a connected and compact two-point homogeneous space, including the special case of the sphere. The ... -
COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning.
(2021-03-19)A multiple objective space-time forecasting approach is presented involving cyclical curve log-regression, and multivariate time series spatial residual correlation analysis. Specifically, the mean quadratic loss function ...