CFO.com

Machine learning improves earnings forecast accuracy by 7%

A new research paper shows the approach performs significantly better than the random-walk forecasting method.

Beyond Blueprints: Why Financial Services AI Governance Needs Both Architecture and Topology

To meet emerging regulatory expectations, AI governance in financial services must incorporate two complementary structural ...
Frontiers

Trajectory tracking for mobile robots based on fractional-order sliding mode and dynamic modeling

Introduction: Trajectory tracking control is a core link to ensure the normal operation of robots. However, traditional trajectory tracking control methods have problems such as low operational ...
IEEE

Approximate Nonlinear Model Predictive Control With Safety-Augmented Neural Networks

Abstract: Model predictive control (MPC) achieves stability and constraint satisfaction for general nonlinear systems but requires computationally expensive online optimization. This brief studies ...
IEEE

Practical Nonlinear Model Predictive Control With Kolmogorov–Arnold Network Models

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 ...
Renewable Energy World

Network model management: Collaboration in and out of the control room

The global energy sector is undergoing a transformation, with the electric grid expanding to accommodate an increasing number of assets, including solar arrays, wind farms, batteries, electric ...
Automation

Tutorial - Simple Nonlinear Model-Based Process Control

ISA 2012 Automation Week Track: Control Performance Thursday, 27 September, 3:15-4:45 pm, Room 204B R. Russell Rhinehart School of Chemical Engineering, Oklahoma State University Often, nonlinearity ...