Multiscale Bayesian neural networks for soil water content estimation

Water Resources Research

Volumn 44, Issue 8, 2008, Pages

  Jana, Raghavendra B ^a   Mohanty, Binayak P ^a   Springer, Everett P ^b  

^a Texas A and M University   (United States)

^b LOS ALAMOS NATIONAL LABORATORY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL INTELLIGENCE; BACKPROPAGATION; EARTH SCIENCES; ELASTIC MODULI; ELECTRIC FAULT LOCATION; FLUID MECHANICS; FORECASTING; FORESTRY; GEOLOGIC MODELS; GROUND PENETRATING RADAR SYSTEMS; HYDRAULIC TOOLS; HYDRAULICS; NETWORK PROTOCOLS; NEURAL NETWORKS; PARAMETER ESTIMATION; SENSOR NETWORKS; SOIL MOISTURE; SOIL SURVEYS; SOILS; UNDERWATER SOILS; WATER; WATER CONTENT;

ARTIFICIAL NEURAL NETWORKS; BAYESIAN; BAYESIAN FRAMEWORKS; BAYESIAN NEURAL NETWORKS; BAYESIAN TECHNIQUES; BULK DENSITIES; CONTAMINANT TRANSPORT; DOWN-SCALING; GRID SIZES; HYDROCLIMATIC; INPUT DATA; LOCAL SCALING; MULTI SCALING; NEW MEXICO; NONLINEAR BIAS; NONLINEAR CORRECTION; OKLAHOMA; PEDOTRANSFER FUNCTIONS; PRESSURE HEADS; RECENT DEVELOPMENTS; RIO GRANDE; SOIL DATA; SOIL HYDRAULIC PARAMETERS; SOIL HYDRAULIC PROPERTIES; SOIL PHYSICAL PROPERTIES; SOIL PROPERTIES; SOIL TEXTURES; SOIL WATER CONTENT; SOIL-WATER CONTENTS; SOIL-WATER RETENTION; SOUTHERN GREAT PLAINS; SPATIAL SCALING; STUDY AREAS; STUDY SITES; UNITED STATES; VALIDATION DATA;

BAYESIAN NETWORKS;

ARTIFICIAL NEURAL NETWORK; BAYESIAN ANALYSIS; DATABASE; DOWNSCALING; ESTIMATION METHOD; EXPERIMENTAL STUDY; HYDRAULIC PROPERTY; PEDOTRANSFER FUNCTION; SOIL PROPERTY; SOIL SURVEY; SOIL WATER; WATER CONTENT;

GREAT PLAINS; LAS CRUCES; NEW MEXICO; NORTH AMERICA; UNITED STATES;

EID: 53849124012     PISSN: 00431397     EISSN: None     Source Type: Journal    
DOI: 10.1029/2008WR006879     Document Type: Article

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