Performance evaluation of microbial fuel cell by artificial intelligence methods

作者：

Highlights：

• Three artificial intelligence (AI) methods for modeling output voltage of microbial fuel cell (MFC) system is discussed.

• AI models efficiently establish the relationship between output voltage and input factors of MFC.

• Out of three methods, MGGP evolves a model with better generalization ability.

• MGGP shows excellent potential to predict performance of MFC and can be used to gain better insights into MFC system.

摘要

Highlights•Three artificial intelligence (AI) methods for modeling output voltage of microbial fuel cell (MFC) system is discussed.•AI models efficiently establish the relationship between output voltage and input factors of MFC.•Out of three methods, MGGP evolves a model with better generalization ability.•MGGP shows excellent potential to predict performance of MFC and can be used to gain better insights into MFC system.

论文关键词：MFC modeling,MFC prediction,Multi-gene genetic programming,GPTIPS,LS-SVM

论文评审过程：Available online 25 August 2013.

论文官网地址：https://doi.org/10.1016/j.eswa.2013.08.038