Hybrid Neural Network - Finite Element River Flow Model

Journal of Hydraulic Engineering

Volumn 131, Issue 1, 2005, Pages 52-59

  Chua, Lloyd H C ^a,b   Holz, K P ^b  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

^b BRANDENBURG UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

Boundary conditions; Dikes; Finite element method; Hybrid methods; Hydraulic models; Neural networks; River flow

Indexed keywords

HYDRAULIC MODELS; MESH GENERATION; NEURAL NETWORKS; NUMERICAL MODELS; RIVERS; STREAM FLOW; COMPUTATIONAL METHODS; FINITE ELEMENT METHOD; HYDRAULICS; MATHEMATICAL MODELS; REAL TIME SYSTEMS;

FINITE ELEMENT MODELLING (FEM); HYBRID METHOD; HYBRID MODEL; HYBRID NEURAL NETWORK-FINITE ELEMENT MODELS; HYBRID NEURAL NETWORKS; NETWORK NODE; NEURAL-NETWORKS; REAL- TIME; RIVER FLOW; RIVER FLOW MODELS;

FINITE ELEMENT METHOD; FLOW OF WATER;

COMPUTATIONAL NODES; HYBRID NEURAL NETWORK-FINITE ELEMENT MODELS; TWO-DIMENSIONAL SHALLOW WATER EQUATIONS;

BOUNDARY CONDITIONS; FINITE ELEMENT METHOD; NEURAL NETWORK; OPEN CHANNEL FLOW; RIVER ENGINEERING; SHALLOW-WATER EQUATION;

ARTIFICIAL NEURAL NETWORK; BOUNDARY CONDITION; CHANNEL HYDRAULICS; FINITE ELEMENT METHOD; OPEN CHANNEL FLOW; RIVER FLOW; SHALLOW-WATER EQUATION;

EID: 11044233103     PISSN: 07339429     EISSN: 19437900     Source Type: Journal    
DOI: 10.1061/(ASCE)0733-9429(2005)131:1(52)     Document Type: Article

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