Robotics & Machine Learning Daily News2024,Issue(Mar.19) :112-113.DOI:10.1186/s42162-024-00304-8

Research on Machine Learning Reported by Researchers at Leibniz University Hanno ver (ESTSS-energy system time series suite: a declustered, application-independe nt, semi-artificial load profile benchmark set)

Robotics & Machine Learning Daily News2024,Issue(Mar.19) :112-113.DOI:10.1186/s42162-024-00304-8

Research on Machine Learning Reported by Researchers at Leibniz University Hanno ver (ESTSS-energy system time series suite: a declustered, application-independe nt, semi-artificial load profile benchmark set)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – A new study on artificial intelligence is now available. According to news reporting from Leibniz University Hannover by NewsRx journalists, research stated, “This paper introduces an univariate app lication-independent set of load profiles or time series derived from real-world energy system data. The generation involved a two-step process: manifolding the initial dataset through signal processors to increase diversity and heterogenei ty, followed by a declustering process that removes data redundancy.”

Key words

Leibniz University Hannover/Cyborgs/Em erging Technologies/Machine Learning

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