Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices

Energy

Volumn 68, Issue , 2014, Pages 651-657

  Taghavifar, Hamid ^a   Mardani, Aref ^a  

^a URMIA UNIVERSITY   (Iran)

Author keywords

ANN; Energy efficiency; Traction coefficient; Tractive power efficiency

Indexed keywords

LEARNING ALGORITHMS; NEURAL NETWORKS; TRACTION (FRICTION); WHEELS;

ANN; ANN (ARTIFICIAL NEURAL NETWORK); BP (BACK PROPAGATION) ALGORITHM; LEVENBERG-MARQUARDT TRAINING ALGORITHM; OBJECTIVE PARAMETERS; STATISTICAL PERFORMANCE; TRACTION COEFFICIENT; TRACTIVE POWER;

ENERGY EFFICIENCY;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; ENERGY EFFICIENCY; NUMERICAL MODEL; STATISTICAL ANALYSIS; STOCHASTICITY; TOPOLOGY; VELOCITY;

EID: 84898029886     PISSN: 03605442     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.energy.2014.01.048     Document Type: Article

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