The Prediction of Cu(II) Adsorption Capacity of Modified Pomelo Peels Using the PSO-ANN Model

It is very well known that traditional artificial neural networks (ANNs) are prone to falling into local extremes when optimizing model parameters. Herein, to enhance the prediction performance of Cu(II) adsorption capacity, a particle swarm optimized artificial neural network (PSO-ANN) model was de...

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Detalles Bibliográficos
Autores principales: Jiao, Mengqing, Jacquemin, Johan, Zhang, Ruixue, Zhao, Nan, Liu, Honglai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574590/
https://www.ncbi.nlm.nih.gov/pubmed/37836799
http://dx.doi.org/10.3390/molecules28196957

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10574590/
https://www.ncbi.nlm.nih.gov/pubmed/37836799
http://dx.doi.org/10.3390/molecules28196957

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