This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within ...
Abstract: Nonlinear model predictive control (NMPC) algorithms have been widely used in autonomous vehicle trajectory tracking, yet their performance is primarily limited by the accuracy of the ...
Shallem, Greg Ravikovich and Eitan Har-Shoshanim examine how AI addresses the challenge of data overload in solar PV.
Executive Summary - Artificial intelligence has moved from research laboratories into deployed defense systems: autonomous ISR platforms, ...
A new study suggests that lenders may get their strongest overall read on credit default risk by combining several machine learning models rather than relying on a single algorithm. The researchers ...
Abstract: In this article, we propose a self-triggered distributionally robust model predictive control algorithm for linear discrete systems with state chance constraints and unbounded stochastic ...