Abstract: Model predictive current control (MPCC) based on sliding mode disturbance observer (SMDO) effectively addresses the issues arising from parameter mismatches and unmodeled nonlinear elements ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

It’s not very common that a robot the size of a paper clip is able to do ten flips in eleven seconds and keep on course ...

Dr. Bin Tang, Founder & CEO of Noah Digital, is an internationally recognized AI & digital marketing leader & author of “Local to Global.” For years, digital marketing has been synonymous with ...

Imperial College London's Department of Infectious Disease Epidemiology reports a model-predictive control approach that times non-pharmaceutical interventions from noisy real-time case data, ...

A new kind of large language model, developed by researchers at the Allen Institute for AI (Ai2), makes it possible to control how training data is used even after a model has been built.

ABSTRACT: Objective: To develop and validate a machine learning-based risk prediction model for postoperative nausea and vomiting (PONV) following gynecological day hysteroscopy, providing ...

This work extends our prior work on the distributed nonlinear model predictive control (NMPC) for navigating a robot fleet following a certain flocking behavior in unknown obstructed environments with ...

Abstract: Due to the extensive computational burden of enumeration algorithm employed in finite control set model predictive control (FCS-MPC) for multilevel converters, this article proposes a ...

Two new advanced predictive algorithms use information about a person's health conditions and simple blood tests to accurately predict a patient's chances of having a currently undiagnosed cancer, ...