Biosensing with microbial fuel cells and artificial neural networks: Laboratory and field investigations

Journal of Environmental Management

Volumn 130, Issue , 2013, Pages 369-374

  Feng, Yinghua ^a   Harper, Willie F ^b  

^a University of Pittsburgh   (United States)

^b AIR FORCE INSTITUTE OF TECHNOLOGY   (United States)

Author keywords

Biosensing; Inoculation; Methanogenesis; Microbial fuel cells; Neural network algorithms; Water quality

Indexed keywords

MICROBIAL FUEL CELLS; NEURAL NETWORKS; NORMAL DISTRIBUTION;

ANODE-RESPIRING BACTERIA; BIOSENSING; CELL-BASED; FIELD INVESTIGATION; FIELD TESTING; INOCULATION; LABORATORY INVESTIGATIONS; LABORATORY TESTING; METHANOGENESIS; NEURAL NETWORKS ALGORITHMS;

WATER QUALITY;

ACETIC ACID; GLUCOSE; OXYGEN; WATER;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BIOTECHNOLOGY; CHEMICAL OXYGEN DEMAND; CONCENTRATION (COMPOSITION); FUEL CELL; GLUCOSE; INOCULATION; LABORATORY METHOD; METHANOGENESIS; SUBSTRATE; WATER QUALITY;

ANODE RESPIRING BACTERIUM; ARTICLE; ARTIFICIAL NEURAL NETWORK; BACTERIUM; BIOSENSOR; CHEMICAL OXYGEN DEMAND; CONCENTRATION (PARAMETERS); ELECTRIC ACTIVITY; FIELD STUDY; INOCULATION; MICROBIAL FUEL CELL; NONHUMAN; SIGNAL TRANSDUCTION; WATER SAMPLING;

BIOSENSING; INOCULATION; METHANOGENESIS; MICROBIAL FUEL CELLS; NEURAL NETWORK ALGORITHMS; WATER QUALITY;

BIOELECTRIC ENERGY SOURCES; BIOSENSING TECHNIQUES; NEURAL NETWORKS (COMPUTER); WATER MICROBIOLOGY; WATER QUALITY;

EID: 84885360808     PISSN: 03014797     EISSN: 10958630     Source Type: Journal    
DOI: 10.1016/j.jenvman.2013.09.011     Document Type: Article

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