Results 191 to 200 of about 554,064 (360)

New robust two-parameter estimator for overcoming outliers and multicollinearity in Poisson regression model. [PDF]

open access: yesSci Rep
Mohammad HH   +6 more
europepmc   +1 more source

Ellipsoid‐Based Interval‐Type Uncertainty Model Updating Based on Riemannian Manifold and Gaussian Process Model

open access: yesInternational Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT Modern engineering systems require advanced uncertainty‐aware model updating methods that address parameter correlations beyond conventional interval analysis. This paper proposes a novel framework integrating Riemannian manifold theory with Gaussian Process Regression (GPR) for systems governed by Symmetric Positive‐Definite (SPD) matrix ...
Yanhe Tao   +3 more
wiley   +1 more source

Machine learning based model predictive control for grid connected enhanced switched capacitor cross‐connected switched multi‐level inverter (ESC3SMLI)

open access: yesIET Power Electronics, EarlyView., 2023
This article describes an enhanced switched capacitor cross‐connected switched multilevel inverter (ESC3SMLI) with machine learning‐based model‐predictive control (ML‐MPCM). An improved switched capacitor cross connected switched multilevel inverter featuring minimal devices are presented. The proposed ESC3SMLI produces nine levels using eight switches,
Arun Vijayakumar   +4 more
wiley   +1 more source

Dynamics Modeling of Robot Manipulators Based on Deep Lagrangian Network and Torque Separation Technique

open access: yesInternational Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT In recent years, learning robot manipulator dynamics with deep networks has been extensively studied, as it avoids deriving the analytical expression of the robot dynamics equations. In particular, deep Lagrangian networks that incorporate the prior knowledge of Lagrangian mechanics into the deep networks have shown prominent advantages in ...
Xianglong Liang   +3 more
wiley   +1 more source

Optimal Adaptive Reinforcement Learning Control for a Convection‐Reaction Distributed Parameter System

open access: yesOptimal Control Applications and Methods, EarlyView.
Optimal adaptive reinforcement learning control using an actor‐critic architecture. The controller learns optimal control policies online from data measured along the trajectories of a plug flow system ABSTRACT This article is devoted to optimal adaptive control for a distributed parameter convection‐reaction system by reinforcement learning (RL ...
Abdellaziz Binid, Ilyasse Aksikas
wiley   +1 more source

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