Machine learning model development for predicting aeration efficiency through Parshall flume

Sangeeta; Asadollah, SBHS; Sharafati, A; Sihag, P; Al-Ansari, N; Chau, KW

Sharafati, A (corresponding author), Islamic Azad Univ, Dept Civil Engn, Sci & Res Branch, Tehran, Iran.; Al-Ansari, N (corresponding author), Lulea Univ Technol, Civil Environm & Nat Resources Engn, Lulea, Sweden.

ENGINEERING APPLICATIONS OF COMPUTATIONAL FLUID MECHANICS, 2021; 15 (1): 889

Abstract

This study compares several advanced machine learning models to obtain the most accurate method for predicting the aeration efficiency (E-20) through ......

Full Text Link


Links

期刊讨论 | 中国SCI论文 | 期刊主页 | 投稿经验 | 杂志官网 | 投稿链接 | 作者需知 | PMC链接 | Pubmed全文检索