Modeling of a proton exchange membrane fuel cell based on the hybrid particle swarm optimization with Levenberg-Marquardt neural network

Simulation Modelling Practice and Theory

Volumn 18, Issue 5, 2010, Pages 574-588

  Hu, Peng ^a   Cao, Guang Yi ^a   Zhu, Xin Jian ^a   Li, Jun ^a  

^a SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Dynamic behavior; Hybrid particle swarm optimization with Levenberg Marquardt neural network; Modeling; Proton exchange membrane fuel cell

Indexed keywords

COMPLEX NONLINEAR DYNAMICS; CONVERGENT SPEED; DYNAMIC BEHAVIORS; FUEL CELL DESIGNS; GLOBAL OPTIMUM; GLOBAL SEARCH; HYBRID ALGORITHMS; HYBRID PARTICLE SWARM OPTIMIZATION; INITIAL STAGES; LEVENBERG-MARQUARDT; LEVENBERG-MARQUARDT ALGORITHM; LM ALGORITHM; LOCAL MINIMUMS; MODEL TRAINING; NEURAL NETWORK MODELING; NONLINEAR AUTOREGRESSIVE MODEL; NONLINEAR MODELING; PHYSICAL MODEL; PROTON EXCHANGE MEMBRANES; PSO ALGORITHMS; TEMPERATURE MODELS; VALIDATION TEST;

ALGORITHMS; DAMAGE DETECTION; DYNAMIC MODELS; DYNAMICAL SYSTEMS; LAGRANGE MULTIPLIERS; MEMBRANES; MODELS; PARTICLE SWARM OPTIMIZATION (PSO); PROTON EXCHANGE MEMBRANE FUEL CELLS (PEMFC); PROTONS; THREE TERM CONTROL SYSTEMS;

NEURAL NETWORKS;

EID: 77249105911     PISSN: 1569190X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.simpat.2010.01.001     Document Type: Article

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