Using non-parametric statistics to identify the best pathway for supplying hydrogen as a road transport fuel

International Journal of Hydrogen Energy

Volumn 36, Issue 15, 2011, Pages 9382-9395

  Bishop, Justin D K ^a   Axon, Colin J ^b   Banister, David ^b   Bonilla, David ^b   Tran, Martino ^a   McCulloch, Malcolm D ^b  

^a UNIVERSITY OF OXFORD   (United Kingdom)

^b UNIVERSITY OF OXFORD   (United Kingdom)

Author keywords

Adaptive kernel density estimator; Hydrogen; Non parametric statistics; Well to tank

Indexed keywords

ADAPTIVE KERNELS; BEST ESTIMATES; CROSS VALIDATION; DATA SETS; ENERGY EFFICIENT; ENERGY IMPACT; HYDROGEN PRODUCTION PROCESS; HYDROGEN SUPPLY; LEAST SQUARE; MULTIMODAL FEATURES; NON-GAUSSIAN; NON-PARAMETRIC STATISTICAL METHODS; NON-PARAMETRIC STATISTICS; PLUG-INS; PRODUCTION PATHWAYS; RENEWABLES; ROAD TRANSPORTS; SECOND GENERATION; STATISTICAL DISTRIBUTION; WELL-TO-TANK;

ELECTROLYSIS; ESTIMATION; GAS EMISSIONS; GLOBAL WARMING; GREENHOUSE GASES; HYDROGEN PRODUCTION; LEAST SQUARES APPROXIMATIONS; PARAMETER ESTIMATION; PROBABILITY DENSITY FUNCTION; PROBABILITY DISTRIBUTIONS; STEAM ENGINEERING; STEAM REFORMING; TANKS (CONTAINERS);

HYDROGEN;

EID: 79958818044     PISSN: 03603199     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ijhydene.2011.04.173     Document Type: Article

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