Artículo

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

Resumen

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 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 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.
Bao, Haoran (59488973200); Nikolaeva, Anna (59489398100); Xia, Jun (59148841500); Ma, Feng (59489188000)
Evolution Trends and Future Prospects in Artificial Marine Reef Research: A 28-Year Bibliometric Analysis
2025
10.3390/su17010184
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214475018&doi=10.3390%2fsu17010184&partnerID=40&md5=de023fd8f5c61e9bce1810c36393d7db
Department of Marine and Fisheries Business Administration, Pukyong National University, Busan, 48513, South Korea; School of Economics and Management, Nanjing Forestry University, Nanjing, 210037, China; Department of Marine Design Convergence Engineering, Pukyong National University, Busan, 48513, South Korea; Department of Environmental Design, Dongseo University, Busan, 47011, South Korea; College of Network Communication, Zhejiang Yuexiu University of Foreign Languages, Shaoxing, 312000, China
All Open Access; Gold Open Access
Scopus
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