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 ...

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 ...

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 ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this research work authors have experimentally validated a blend of Machine ...