Sensitivity analysis of artificial neural networks for just-suspension speed prediction in solid-liquid mixing systems: Performance comparison of MLPNN and RBFNN-Reference-Cited by-同舟云学术

Sensitivity analysis of artificial neural networks for just-suspension speed prediction in solid-liquid mixing systems: Performance comparison of MLPNN and RBFNN

Published:2019-01 Issue: Volume:39 Page:278-291
ISSN:1474-0346
Container-title:Advanced Engineering Informatics
language:en
Short-container-title:Advanced Engineering Informatics

Author:

Ibrahim Shaliza,Choong Choe Earn,El-Shafie Ahmed^ORCID

Funder

University of Malaya Research Grant

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems

Reference31 articles.

1. Solid suspension and liquid phase mixing in solid−liquid stirred tanks;Sardeshpande;Ind. Eng. Chem. Res.,2009

2. Mixing intensification for the mineral industry;Wu;Can. J. Chem. Eng.,2010

3. Suspending of solid particles in liquid by agitators;Zwietering;Chem. Eng. Sci.,1958

4. Solid-Liquid Mixing, Handbook of Industrial Mixing;Atiemo-Obeng,2004

5. Characterization of minimum impeller speed for suspension of solids in liquid at high solid concentration, using gamma-ray densitometry;Jafari;Int. J. Chem. Eng.,2012

Cited by 24 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Study on penetration depth in laser welding: A process information database-based control strategy and OCT measuring verification;Advanced Engineering Informatics;2024-10

2. New strategy to optimize in-situ fenton oxidation for TPH contaminated soil remediation via artificial neural network approach;Chemosphere;2024-09

3. The ANN Architecture Analysis: A Case Study on Daylight, Visual, and Outdoor Thermal Metrics of Residential Buildings in China;Buildings;2023-11-07

4. Quantitative analysis and early detection of postharvest soft rot in kiwifruit using E-nose and chemometrics;Journal of Food Measurement and Characterization;2023-06-01

5. Novel Correlation for Critical Speed for Solid Suspension in Stirred Tanks Developed Using Machine Learning Models Trained on Literature Data;Industrial & Engineering Chemistry Research;2023-05-24