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A reduced model for phase-change problems with radiation using simplified PN approximations
Published 2025“…The integro-differential equation for the full radiative transfer is replaced by a set of differential equations which are independent of the angle variable and easy to solve using conventional computational methods. To solve the coupled equations, we implement a second-order implicit scheme for the time integration and a mixed finite element method for the space discretization. …”
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Learning continuous functions using decision tree learning algorithms
Published 2001Get full text
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Block constrained pressure residual preconditioning for two-phase flow in porous media by mixed hybrid finite elements
Published 2023“…This preconditioner, denoted as Block CPR (BCPR), is specifically designed for Lagrange multipliers-based flow models, such as those generated by Mixed Hybrid Finite Element (MHFE) approximations. …”
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Teaching–learning-based optimization algorithm: analysis study and its application
Published 2024Subjects: “…Teaching–learning-based optimization algorithm…”
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A discrete-time learning control algorithm
Published 1994“…A discretized version of the D-type learning control algorithm is presented for a MIMO linear discrete-time system. …”
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Extended Behavioral Modeling of FET and Lattice-Mismatched HEMT Devices
Published 2016Subjects: Get full text
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Learning control algorithms for tracking "slowly" varying trajectories
Published 1997“…This is due to the requirement that all learning algorithms assume that a desired output is given a priori over the time duration t /spl isin/ ~0,T\. …”
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Selection of the learning gain matrix of an iterative learning control algorithm in presence of measurement noise
Published 2005“…This work also provides a recursive algorithm that generates the appropriate learning gain functions that meet the arbitrary high precision output tracking objective. …”
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Optimal selection of the forgetting matrix into an iterative learning control algorithm
Published 2005“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the optimal forgetting matrix and the learning gain matrix of a P-type iterative learning control (ILC) for linear discrete-time varying systems with arbitrary relative degree. …”
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Exploring Semi-Supervised Learning Algorithms for Camera Trap Images
Published 2022“…A Master of Science thesis in Computer Engineering by Ali Reza Sajun entitled, “Exploring Semi-Supervised Learning Algorithms for Camera Trap Images”, submitted in August 2022. …”
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Accommodating High Penetrations of Renewable Distributed Generation Mix in Smart Grids
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A stochastic iterative learning control algorithm with application to an induction motor
Published 2004“…A recursive optimal algorithm, based on minimizing the input error covariance matrix, is derived to generate the learning gain matrix of a P-type ILC for linear discrete-time varying systems with arbitrary relative degree. …”
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