Bibliometric analysis of artificial intelligence algorithms used for microbial fuel cell research

Bibliometric analysis of artificial intelligence algorithms used for microbial fuel cell research

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Research regarding microbial fuel cells has been stimulated to reduce the operating costs and energy consumption of conventional wastewater treatment, and increase its profitability.However, these devices are challenging to study due to their complexity and sensitivity to both internal and external factors.Artificial intelligence (AI) has been used to analyze microbial fuel cells as an effective alternative to the use of mathematical models, which are still in development.In this study, the main goals were to perform the first bibliometric analysis of AI applied to microbial fuel cell research and to find the most popular algorithms used to date.Using the Web of Science database, a read more total of 102 articles published between 1999 and 2022 were retrieved.

The cumulative number of articles has greatly increased over the past 10 years.About 55% were contributed by researchers from China and USA, leading among 20 countries.Some sapatilha infantil prata glitter 50 algorithms were used, with principal component analysis and feed-forward neural networks being the most popular used to study and optimize microbial fuel cells.HIGHLIGHTS The first bibliometric analysis of applied to microbial fuel cell research was performed.; The number of publications has grown exponentially since 2013.

; 102 articles were published between 1999 and 2022.; 50 AI algorithms have been used in microbial fuel cell research.; The most popular algorithms are principal component analysis and feed-forward neural networks.;.