A data-driven approach for modeling post-fire debris-flow volumes and their uncertainty

Environmental Modelling and Software

Volumn 26, Issue 12, 2011, Pages 1583-1598

  Friedel, Michael J ^a  

^a DENVER FEDERAL CENTER   (United States)

Author keywords

Debris flow volume; Genetic programming; Multivariate; Nonlinear models; Nonlinear uncertainty; Prediction; Self organizing map; Wildfire

Indexed keywords

DEBRIS-FLOW VOLUME; MULTIVARIATE; NON-LINEAR MODEL; NONLINEAR UNCERTAINTIES; SELF ORGANIZING; WILDFIRE;

CONFORMAL MAPPING; DEBRIS; FORECASTING; GENETIC PROGRAMMING; LINEAR REGRESSION; RAIN; REACTOR CORES; STORMS; UNCERTAINTY ANALYSIS;

NONLINEAR EQUATIONS;

DEBRIS FLOW; FLOW VELOCITY; GENETIC ALGORITHM; MULTIVARIATE ANALYSIS; NONLINEARITY; OPTIMIZATION; PREDICTION; RAINFALL; RAINSTORM; REGRESSION ANALYSIS; SLOPE ANGLE; UNCERTAINTY ANALYSIS; WILDFIRE;

UNITED STATES;

EID: 84855487286     PISSN: 13648152     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.envsoft.2011.07.014     Document Type: Article

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