An improved TOPSIS-based multi-criteria decision-making approach for evaluating the working condition of the aluminum reduction cell
Authors:
- Zhaoke HuangZHZhaoke Huang
- Chunhua YangCYChunhua Yang
- Xiaojun ZhouXZXiaojun Zhou
- Weihua GuiWGWeihua Gui
- 22 November 2022
- journal article
- research article
- Published by Elsevier in Engineering Applications of Artificial Intelligence
- Vol. 117
Abstract
No abstract availableKeywords
This publication has 37 references indexed in Scilit:
- Evaluation strategy and mass balance for making decision about the amount of aluminum fluoride addition based on superheat degreeJournal of Industrial and Management Optimization, 2020
- p-Arsanilic acid degradation and arsenic immobilization by a disilicate-assisted iron/aluminum electrolysis processChemical Engineering Journal, 2019
- Survey on fuzzy TOPSIS state-of-the-art between 2007 and 2017Computers & Operations Research, 2019
- Multimode process monitoring based on robust dictionary learning with application to aluminium electrolysis processNeurocomputing, 2019
- Operating Parameters Optimization for the Aluminum Electrolysis Process Using an Improved Quantum-Behaved Particle Swarm AlgorithmIEEE Transactions on Industrial Informatics, 2017
- A knowledge reasoning Fuzzy-Bayesian network for root cause analysis of abnormal aluminum electrolysis cell conditionFrontiers of Chemical Science and Engineering, 2017
- A state-of the-art survey of TOPSIS applicationsExpert Systems with Applications, 2012
- Sensitivity analysis of TOPSIS method in water quality assessment: I. Sensitivity to the parameter weightsEnvironmental Monitoring and Assessment, 2012
- Aluminium process fault detection by Multiway Principal Component AnalysisControl Engineering Practice, 2011
- Determining objective weights in multiple criteria problems: The critic methodComputers & Operations Research, 1995