Neural network approach for robust and fast calculation of physical processes in numerical environmental models: Compound parameterization with a quality control of larger errors

Neural Networks

Volumn 21, Issue 2-3, 2008, Pages 535-543

  Krasnopolsky, Vladimir M ^a,b   Fox Rabinovitz, Michael S ^b   Tolman, Hendrik L ^c   Belochitski, Alexei A ^b  

^a SAIC FREDERICK INC   (United States)

^b Bldg 142   (United States)

^c NOAA EARTH SYSTEM RESEARCH LABORATORY   (United States)

Author keywords

Climate; Data assimilation; Neural networks; Numerical modeling; Waves; Weather

Indexed keywords

COMPUTER SIMULATION; DATA ACQUISITION; NUMERICAL METHODS; PARAMETERIZATION; WEATHER FORECASTING;

COMPOUND PARAMETERIZATION; DATA ASSIMILATION; NUMERICAL MODELING;

NEURAL NETWORKS;

ACCURACY; ANALYTIC METHOD; ANALYTICAL ERROR; ARTICLE; ARTIFICIAL NEURAL NETWORK; CALCULATION; CLIMATE; CLIMATE CHANGE; COMPOUND PARAMETERIZATION; ENVIRONMENT; PHYSICS; PREDICTION; PRIORITY JOURNAL; QUALITY CONTROL; QUANTITATIVE STUDY; VALIDATION STUDY;

ARTIFICIAL INTELLIGENCE; CLIMATE; COMPUTER SIMULATION; ENVIRONMENT; MODELS, STATISTICAL; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; NUMERICAL ANALYSIS, COMPUTER-ASSISTED; SPECTRUM ANALYSIS; WEATHER;

EID: 40649127675     PISSN: 08936080     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neunet.2007.12.019     Document Type: Article

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