Manufacturing technologies have been the first domain to experience this transformation. The review documents how artificial ...

The strong role of socioeconomic factors underscores the limits of purely spatial or technical solutions. While predictive models can identify where risk concentrates, addressing why it does so ...

Using AI and machine learning as transformative solutions for semiconductor device modeling and parameter extraction.

A new AI developed at Duke University can uncover simple, readable rules behind extremely complex systems. It studies how ...

Discover the methods that companies use for forecasting oil prices, including calculus, econometrics, and market influences like OPEC and futures trading.

The study of quantum chaos reveals its early emergence in quantum processors, affecting information scrambling and the ...

A research team at Duke University has developed a new AI framework that can uncover simple, understandable rules that govern ...

This new AI acts like a digital scientist, turning messy data into simple rules that explain how the world really works.

Abstract: State estimation for nonlinear models has been a longstanding challenge in the field of signal processing. Classical nonlinear filters, such as the extended Kalman filter (EKF), unscented ...

This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...

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 ...

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 ...