Optimization of anaerobic digestion through automatic control with neural networks: a bibliometric analysis

Abstract

The present work was carried out with the objective of presenting the current importance of work related to the optimization of anaerobic digesters using artificial neural networks. A scientometric methodological approach was used for a systematic review of the publications indexed in Scopus until 2023. The H index was used to evaluate the visibility and impact of the journals, authors, countries, and institutions with the highest levels of production and recognition in the field of study. This review also allowed us to analyze the interaction between groups and knowledge networks with the authors and institutions identified in the classification. The results show a significant increase in the number of publications between the years 1973 and 2023, which allow us to characterize on a scale the main dimensions of research, development and innovation related to the study of optimization methods of anaerobic biodigesters for the production of biogas from different waste such as that from the palm oil extraction process. The results show a significant increase in the number of publications between 2016 and 2023, a total of 2847 documents were found, where 95.64% are in English. The country that presents the most publications on the topic is China with a contribution of 19.28%, followed by the United States with 9.8%, India with 7.2% and Spain with 6.2% among others.