Designing a neural network for closed thermosyphon with nanofluid using a genetic algorithm

Brazilian Journal of Chemical Engineering

Volumn 28, Issue 1, 2011, Pages 157-168

  Salehi, H ^a   Heris, S Zeinali ^a   Salooki, M Koolivand ^a   Noei, S H ^a  

^a FERDOWSI UNIVERSITY OF MASHHAD   (Iran)

Author keywords

Genetic algorithm; Magnetic field; Nanofluid; Neural network; Thermosyphon

Indexed keywords

ARTIFICIAL NEURAL NETWORK; CLOSED THERMOSYPHON; EXPERIMENTAL DATA; INPUT AND OUTPUTS; INPUT PARAMETER; MAGNETIC FIELD STRENGTHS; MATHEMATICAL STRUCTURE; MULTILAYER PERCEPTION NEURAL NETWORKS; NANO-FLUID; NEW APPROACHES; NON-LINEAR RELATIONSHIPS; OUTPUT PARAMETERS; THERMAL EFFICIENCY; THERMAL RESISTANCE; THERMOSYPHONS; TRAINING DATA; TWO-PHASE CLOSED THERMOSYPHON; WORKING FLUID;

CAPILLARY FLOW; GENETIC ALGORITHMS; MAGNETIC FIELDS; NANOFLUIDICS; NANOMAGNETICS; NETWORK LAYERS; SIPHONS;

NEURAL NETWORKS;

EID: 79953071733     PISSN: 01046632     EISSN: None     Source Type: Journal    
DOI: 10.1590/S0104-66322011000100017     Document Type: Article

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