Abstract: To improve the control performance of permanent magnet synchronous motor (PMSM) drive systems, this article proposes a model-free predictive current control method based on adaptive extended ...
More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...
Researchers have developed an advanced artificial intelligence (AI) framework designed to significantly improve the forecasting of carbon dioxide emissions in the aviation sector. ACGRIME is an ...
Adaptive systems were supposed to simplify decision-making. Instead of hard-coded rules, engineers built models that could learn from data, respond to change, and improve over time. That promise still ...
This repository is publicly available on GitHub and provides full access to the source code required to reproduce all experiments reported in the manuscript. The source code has been archived on ...
Abstract: Optimization methods often face a trade-off between the fast convergence of second-order methods and the low computational cost of first-order methods. Motivated by the need to bridge this ...
According to @XPengMotors, the upcoming XPENG P7 features advanced AI-driven systems designed to optimize tire grip and driving stability in winter conditions, leveraging real-time sensor data and ...
ABSTRACT: Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is ...
Artificial deep neural networks (ADNNs) have become a cornerstone of modern machine learning, but they are not immune to challenges. One of the most significant problems plaguing ADNNs is the ...
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