Results 31 to 40 of about 3,518,834 (296)
DECISION MAKING MODELS AND ALGORITHMS IN SITUATIONS OF UNCERTAINTY [PDF]
Economica, 2019 This study describes three decision making models for uncertain situations, when the decision maker has infinity of alternatives, the activity is determined by uncontrollable factors, and the number of states of nature is ...
Lilian GOLBAN, Anatol GODONOAGĂ
doaj
FOCUS: fast Monte Carlo approach to coherence of undulator sources
Journal of Synchrotron Radiation, 2023 FOCUS (Fast Monte CarlO approach to Coherence of Undulator Sources) is a new GPU-based simulation code to compute the transverse coherence of undulator radiation from ultra-relativistic electrons.
M. Siano +10 more
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Efficient neural network training method for unsteady flow field prediction based on data pool
Engineering Applications of Computational Fluid MechanicsIn recent years, neural network technology has made significant progress in the field of unsteady flow field prediction, leading to the development of many innovative methods.
Qiuchi Min +5 more
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Multilevel algorithms for finite difference discretizations on sparse grids
, 2022 S.111-121We propose some algorithms to solve the system of linens equations arising from the finite difference discretization on sparse grids.
Sprengel, F.
core +1 more source
Algorithm to Estimate the Capacity Reserve of Existing Masonry Arch Railway Bridges
Applied Sciences, 2022 Most railway masonry arch bridges were designed according to codes that predate the 1950s; therefore, assessing their load-carrying capacity to comply with current codes is of the utmost importance.
Francesca Brighenti +2 more
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Multi-fidelity learning for atomistic models via trainable data embeddings
Machine Learning: Science and TechnologyWe present an approach for end-to-end training of machine learning models for structure-property modeling on collections of datasets derived using different density functional theory functionals and basis sets. This approach overcomes the problem of data
Rick Oerder +2 more
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Proceedings, 2019 We are developing a software for energy loss simulation which is affected by jets in the nuclear matter described by relativistic hydrodynamics. Our program uses a Cartesian coordinate system in order to provide high spatial resolution for the analysis ...
Marcin Słodkowski +4 more
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Fractal and Fractional, 2022 The paper continues the study of efficient algorithms for the computation of zeta functions over the complex plane. We aim to apply the modifications of algorithms to the investigation of underlying fractal structures associated with the Riemann zeta ...
Igoris Belovas +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Embryonal tumors comprise the majority of malignant central nervous system (CNS) neoplasms diagnosed in children under 3 years of age. Compared with their counterparts in older children, these tumors exhibit distinct molecular biology and a more aggressive clinical phenotype, while their management is complicated by the heightened ...
Sudarshawn Damodharan +3 more
wiley +1 more source
Flexible cutoff learning: optimizing machine learning potentials after training
Machine Learning: Science and TechnologyWe introduce Flexible Cutoff Learning (FCL), a method for training machine learning interatomic potentials (MLIPs) whose cutoff radii can be adjusted after training.
Rick Oerder, Jan Hamaekers
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