International Monetary Fund

GDP Nowcasting Performance of Traditional Econometric Models vs Machine-Learning Algorithms: Simulation and Case Studies

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting?
IEEE

Data-Driven Point-to-Point Finite-Iteration Learning Control for a Class of Nonlinear Systems With Output Saturation

Abstract: This article considers the point-to-point tracking control problem for a class of unknown nonlinear discrete-time systems with output saturation. A novel data-driven finite-iteration ...
Devdiscourse

Advanced AI system accurately forecasts ecological strain over three decades

Their study presents a new combination of computational tools that merges the Chinese Pangolin Optimizer (CPO) with the ...
IEEE

An Adaptive-Gain Reinforcement Iterative Learning Control Scheme for Nonlinear Systems to Track Morphologically Similar Targets

Abstract: This paper investigates the problem of tracking morphologically similar targets for nonlinear systems and proposes an adaptive-gain reinforcement iterative learning control (AG-RILC) scheme.
Journal of Medical Internet Research

Machine Learning–Based Explainable Automated Nonlinear Computation Scoring System for Health Score and an Application for Prediction of Perioperative Stroke: Retrospective Study

Background: Machine learning (ML) has the potential to enhance performance by capturing nonlinear interactions. However, ML-based models have some limitations in terms of interpretability. Objective: ...