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The RBF neural network and ELM neural network were used to perform nonlinear system regression in the later stage of SMFC start-up and using the regression network to forecast part of the data.The experimental results show that the ELM neural network is more excellent in forecasting SMFC system.In the process of microbial fuel cell start-up, the relationship between temperature, p H, and voltage was analysed in detail, and the correlation between them was calculated using SPSS software.
Compared with MFC, Sediment microbial fuel cells (SMFCs) are a special application of MFCs for sustainable electricity production  and are also the most common membrane free microbial fuel cells which are considered as alternative renewable energy sources for remote environmental monitoring via an energy conversion system.
SMFC generates electrical energy through the oxidation of organic matter in the presence of fermentative bacteria under mild operating conditions .
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Sediment microbial fuel cells (SMFCs) are a typical microbial fuel cell without membranes.
The cathode operating conditions play an important part in the overall performance of the MFC .
Cathodic p H microenvironment is one of the crucial factors affecting the metabolic activity of the substrate, affecting the electron and H reaction mechanism.
There is also no advanced monitoring method to monitor the minute changes of the parameters in the start-up process on-line.
This will lead to the loss of important data in the detection process and will consume a lot of manpower and material resources which will bring inconvenience to the intensive study of SMFC.
However, the low output power density of MFC is generally not enough to drive common electronic devices continuously and extremely hinder its practical application [11, 12].
In recent years, researchers in various countries have studied MFC in terms of microorganisms, electrodes, configurations, matrices, operating conditions, and electrochemical properties and found that although microorganisms are the core of MFC, nonbiological factors are more important than biological factors in the production of electricity .