Solving initial-boundary value problems for systems of partial differential equations using neural networks and optimization techniques

Journal of the Franklin Institute

Volumn 346, Issue 9, 2009, Pages 898-913

  Shekari Beidokhti, R ^a   Malek, A ^a  

^a TARBIAT MODARES UNIVERSITY   (Iran)

Author keywords

Feed forward artificial neural networks; Initial boundary value problems; Multidimensional optimization; Time dependent system of partial differential equations

Indexed keywords

ADJUSTABLE PARAMETERS; APPROXIMATE SOLUTION; ARTIFICIAL NEURAL NETWORK; BIHARMONIC EQUATIONS; COLLOCATION METHOD; FEED FORWARD ARTIFICIAL NEURAL NETWORKS; HYBRID METHOD; INITIAL VALUES; INITIAL-BOUNDARY VALUE PROBLEMS; MULTIDIMENSIONAL OPTIMIZATION; NUMERICAL EFFICIENCY; OPTIMAL VALUES; OPTIMIZATION TECHNIQUES; SYSTEMS OF PARTIAL DIFFERENTIAL EQUATIONS; TEST PROBLEM; TIME-DEPENDENT PARTIAL DIFFERENTIAL EQUATIONS; TIME-DEPENDENT SYSTEM OF PARTIAL DIFFERENTIAL EQUATIONS;

BACKPROPAGATION; COMPUTATIONAL FLUID DYNAMICS; FORCE MEASUREMENT; HYBRID SENSORS; INITIAL VALUE PROBLEMS; NEURAL NETWORKS; OPTIMIZATION; ORDINARY DIFFERENTIAL EQUATIONS; PARTIAL DIFFERENTIAL EQUATIONS;

BOUNDARY CONDITIONS;

EID: 70349778465     PISSN: 00160032     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfranklin.2009.05.003     Document Type: Article

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