Abstract: This paper presents a novel approach to practical nonlinear model predictive control (PNMPC) using Kolmogorov–Arnold networks (KANs) as prediction models. KANs are based on the ...

Risk prediction has been used in the primary prevention of cardiovascular disease for >3 decades. Contemporary cardiovascular risk assessment relies on multivariable models, which integrate ...

Escola de Química, EPQB, Universidade Federal do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro 21941-909, Brazil Programa de Engenharia Química, PEQ/COPPE, Universidade Federal do Rio de Janeiro, Rio ...

Objective: To establish a secondary prevention screening model for predicting metabolic syndrome (MetS) based on community obstructive sleep apnea (OSA) screening, using simple and easily accessible ...

Abstract: To mitigate parameter sensitivity of the permanent magnet synchronous motor (PMSM) under the model predictive control (MPC), a simple motor-parameter-free model predictive voltage control ...

During the peer-review process the editor and reviewers write an eLife assessment that summarises the significance of the findings reported in the article (on a scale ranging from landmark to useful) ...

Introduction: This work presents an approach to collision avoidance in multi-agent systems (MAS) by integrating Conflict-Based Search (CBS) with Model Predictive Control (MPC), referred to as Conflict ...

To drive growth, companies should transform customer support from reactive to predictive and proactive. Using foresight, ethical data and strategic alignment can turn customer experience into a key ...