Reports on Support Vector Machines from University of Shanghai for Science and T echnology Provide New Insights (Pm2.5 Collection Efficiency of Wire-plate Electr ostatic Precipitator: Prediction of Temperature Effects Using Support …)

Robotics & Machine Learning Daily News2024，Issue(Apr.9) ：73-74.

来源：

NETL
NSTL

Reports on Support Vector Machines from University of Shanghai for Science and T echnology Provide New Insights (Pm2.5 Collection Efficiency of Wire-plate Electr ostatic Precipitator: Prediction of Temperature Effects Using Support …)

扫码查看

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews – Investigators discuss new findings in Support Vec tor Machines. According to news reportingoriginating in Shanghai, People’s Repu blic of China, by NewsRx journalists, research stated, “With therapid developme nt of industry, coal-fired power generation accounts for a large proportion of t he totalpower generation, emitting a large amount of harmful substances, such a s PM2.5, seriously affectinghuman health. To investigate the PM2.5 collection e fficiency of wire-plate electrostatic precipitator (ESP)at different temperatur es, numerical simulations based on the multi-field coupling model of ESP were conducted.”

Key words

Shanghai/People’s Republic of China/As ia/Algorithms/Emerging Technologies/Machine Learning/Particle Swarm Optimiza tion/Support Vector Machines/Vector Machines/University of Shanghai for Scien ce and Technology

引用本文复制引用

出版年

2024

Robotics & Machine Learning Daily News

ISSN：

段落导航