Evaluation of artificial neural network algorithms for predicting the effect of the urine flow rate on the power performance of microbial fuel cells. (2020)

First Author: De Ramón-Fernández A
Attributed to:  MFC Commercialisation through continued Research, Networking and Collaboration (MFCC-RNC) funded by EPSRC

Abstract

No abstract provided

Bibliographic Information

Digital Object Identifier: http://dx.doi.org/10.1016/j.energy.2020.118806

PubMed Identifier: 33335352

Publication URI: http://europepmc.org/abstract/MED/33335352

Type: Journal Article/Review

Volume: 213

Parent Publication: Energy (Oxford, England)

ISSN: 0360-5442