Robotics & Machine Learning Daily News2024,Issue(Oct.15) :87-88.

Reports from Xiangtan University Describe Recent Advances in Machine Learning (B ackward Differentiation Formula Method and Random Forest Method To Solve Continu ous-time Differential Riccati Equations)

Robotics & Machine Learning Daily News2024,Issue(Oct.15) :87-88.

Reports from Xiangtan University Describe Recent Advances in Machine Learning (B ackward Differentiation Formula Method and Random Forest Method To Solve Continu ous-time Differential Riccati Equations)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Investigators publish new report on Ma chine Learning. According to news originating from Xiangtan, People’s Republic o f China, by NewsRx correspondents, research stated, “In this paper, we explore t he utilization of machine learning techniques for solving the numerical solution s of continuoustime differential Riccati equations.”Financial support for this research came from National Key Research & Development Program of China. Our news journalists obtained a quote from the research from Xiangtan University , “Specifically, we focus on generating a reduction matrix capable of transformi ng a high-order matrix into a low-order matrix. Additionally, we address the iss ue of differential terms in the continuous-time differential Riccati equation an d incorporate the backward differentiation formula of the matrix to improve stab ility and accuracy.”

Key words

Xiangtan/People’s Republic of China/As ia/Cyborgs/Emerging Technologies/Machine Learning/Xiangtan University

引用本文复制引用

出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
段落导航相关论文