A Survey of Applications of MFC and Recent Progress of Artificial Intelligence and Machine Learning Techniques and Applications, with competing fuel cells. (1st June 2022)

• Record Type: Journal Article
• Authors: Gyaneshwar, Amogh; Selvaraj, Senthil Kumaran; Ghimire, Turusha; Mishra, Saumya Jayanti; Gupta, Shaily; Chadha, Utkarsh; Manoharan, Manikandan; Paramasivam, Velmurugan
• Is Part Of: Engineering research express. Volume 4:Number 2(2022)
• Publication Date: 2022-06-01
• Subjects: microbial fuel cell -- artificial intelligence -- machine learning; Engineering -- Periodicals; 620.005
• DOI: 10.1088/2631-8695/ac5fd9
• Languages: English
• ISSNs: 2631-8695

Abstract

Abstract: Tomorrow is a technology for Microbial fuel cells (MFC). It has attracted numerous studies for the continuous development of cell efficiency since the problem of the coming era can be resolved. Implementing artificial learning and machine learning is a change that can effectively achieve the goals. A microbial fuel cell is a complex non-linear procedure that preferably requires a strategy that is not a linear control strategy for the most favorable outcome. The practical and feasible ways to tackle non-linearity existing in the Microbial Fuel Cell, instead of making a computationally tedious and heavy non-linear control strategy a superior single linear model or scheduling or multiple model-oriented control techniques. Machine learning and Artificial Intelligence help reduce computation and model costs. It saves time and is more efficient than previously used manual methods, which are now obsolete. In order to find the most accurate results, the study would compare all currently available research efforts and focus on implementing Artificial Intelligence and Machine learning concepts within the Microbial Fuel Cell and comparison with other fuel cells.