Prediction and assimilation of surf-zone processes using a Bayesian network. Part II: Inverse models

Coastal Engineering

Volumn 58, Issue 3, 2011, Pages 256-266

  Plant, Nathaniel G ^a   Holland, K Todd ^b  

^a U S GEOLOGICAL SURVEY   (United States)

^b NAVAL RESEARCH LABORATORY   (United States)

Author keywords

Bathymetry; Duck94; Field data; Parameter estimation; Wave height

Indexed keywords

BAYESIAN; BAYESIAN MODEL; BAYESIAN NETWORK MODELS; DATA ASSIMILATION; DEPTH INFORMATION; DUCK94; FIELD DATA; INVERSE METHODS; INVERSE MODELING; INVERSE MODELS; LONG TIME SERIES; MODEL DOMAINS; MODEL PARAMETERS; OFFSHORE WAVES; ONSHORE LOCATIONS; PREDICTION ERRORS; PROCESS MODEL; SENSING SYSTEMS; SURF ZONES; TUNING PARAMETER; UNCERTAINTY ESTIMATES; WATER DEPTH; WAVE HEIGHT; WAVE HEIGHTS; WAVEBREAKING;

BATHYMETRY; BAYESIAN NETWORKS; DATA PROCESSING; DISTRIBUTED PARAMETER NETWORKS; FORECASTING; INFERENCE ENGINES; INTELLIGENT NETWORKS; INVERSE PROBLEMS; OCEANOGRAPHY; REACTOR CORES; REMOTE SENSING; TIME SERIES; UNCERTAINTY ANALYSIS; WATER WAVES; WAVE PROPAGATION;

PARAMETER ESTIMATION;

BATHYMETRY; BAYESIAN ANALYSIS; DATA ASSIMILATION; ERROR ANALYSIS; FIELD METHOD; INVERSE ANALYSIS; PARAMETERIZATION; PREDICTION; REMOTE SENSING; SURF ZONE; WAVE BREAKING; WAVE HEIGHT; WAVE MODELING; WAVE PROPAGATION;

EID: 78650622372     PISSN: 03783839     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.coastaleng.2010.11.002     Document Type: Article

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