Optimización de la digestión anaerobia mediante control automático con redes neuronales: un análisis bibliométrico
DOI:
https://doi.org/10.15649/2346030X.3891Palabras clave:
optimización, digestión anaerobia, ARN, bibliometría, análisis bibliométrico, índice H, scopusResumen
El presente trabajo se realizó con el objetivo de presentar la importancia actual de los trabajos relacionados con la optimización de digestores anaerobios utilizando redes neuronales artificiales. Se utilizó un enfoque metodológico cienciométrico para una revisión sistemática de las publicaciones indexadas en Scopus hasta 2023. Se utilizó el índice H para evaluar la visibilidad e impacto de las revistas, autores, países e instituciones con mayores niveles de producción y reconocimiento en el campo de estudio. Esta revisión también permitió analizar la interacción entre grupos y redes de conocimiento con los autores e instituciones identificados en la clasificación. Los resultados muestran un incremento significativo en el número de publicaciones entre los años 1973 y 2023, que nos permiten caracterizar a escala las principales dimensiones de la investigación, desarrollo e innovación relacionadas con el estudio de métodos de optimización de biodigestores anaerobios para la producción de biogás a partir de diferentes residuos como el procedente del proceso de extracción del aceite de palma. Los resultados muestran un aumento significativo en el número de publicaciones entre 2016 y 2023, se han encontrado un total de 2847 documentos, donde el 95,64% están en inglés. El país que más publicaciones presenta sobre el tema es China con una contribución del 19,28%, seguido de Estados Unidos con un 9,8%, India con un 7,2% y España con un 6,2% entre otros.
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