Event-triggered self-regulating integrated PID extreme optimization and fault-tolerant strategy for floating offshore platforms driven by TBG-EDF dual finite-time learning mechanism. [PDF]
Chao C, Liu Y, Wang Z.
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Hybrid deep feature integration model for robust deepfake detection using transfer-learned neural networks. [PDF]
Potluri S +5 more
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Scenario-based portfolio optimization via bootstrapping and machine learning methods: Theory development and empirical evidence from the Tehran Stock Market. [PDF]
Amini M, Javadi S, Soleimani-Damaneh M.
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Deep Reinforcement Learning-Based Intelligent Water Level Control: From Simulation to Embedded Implementation. [PDF]
Cusihuallpa-Huamanttupa K +6 more
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Contextual quantum neural networks for stock price prediction. [PDF]
Mourya S, Leipold H, Adhikari B.
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Fragen der numerischen Integration bei stochastischen Finiten Elementen für nichtlineare Probleme: Erweiterte Version eines Vortrages auf der "International Conference on the Applications of Computer Sciences and Mathematics, Architecture and Civil Engineering (IKM 2003)", Weimar, 2003 [PDF]
We describe methods for the numerical solution of nonlinear problems with stochastic uncertainties in the operator, boundary conditions, and right hand side. First, we compute statistics of the solution directly as high-dimensional integrals and compare their evaluation by sparse (Smolyak) quadrature and Monte Carlo integration. Subsequently, we employ
Keese, Andreas, Matthies, Hermann G.
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Mapping the problems of computational mathematics onto computer systems architecture
Russian Journal of Numerical Analysis and Mathematical Modelling, 2000Summary: We consider the main concepts of the main line of investigation which is called `Mapping the problems of computational mathematics onto computer systems architecture'. We analyze the association of this trend with various fields that somehow deal with computations: analysis of round-off errors, fast computations, algorithm structure, programs ...
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