Monthly streamflow forecasting using Gaussian process regression

Journal of Hydrology

Volumn 511, Issue , 2014, Pages 72-81

  Sun, Alexander Y ^a   Wang, Dingbao ^b   Xu, Xianli ^c  

^a UNIVERSITY OF TEXAS AT AUSTIN   (United States)

^b University of Central Florida   (United States)

^c INSTITUTE OF GEOLOGY AND GEOPHYSICS   (China)

Author keywords

Gaussian Process Regression; Hydrologic similarity; Machine learning theory; Probabilistic streamflow forecasting; Water energy interactions

Indexed keywords

ARTIFICIAL NEURAL NETWORK MODELS; GAUSSIAN PROCESS REGRESSION; HYDROLOGIC SIMILARITY; MULTIVARIATE GAUSSIAN DISTRIBUTIONS; POSTERIOR DISTRIBUTIONS; STREAMFLOW FORECASTING; WATER RESOURCES MANAGEMENT; WATER RESOURCES PLANNING AND MANAGEMENTS;

CLIMATE CHANGE; FORECASTING; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); LEARNING ALGORITHMS; LEARNING SYSTEMS; NEURAL NETWORKS; RANDOM PROCESSES; REGRESSION ANALYSIS; WATER RESOURCES;

STREAM FLOW;

ALGORITHM; BAYESIAN ANALYSIS; FORECASTING METHOD; GAUSSIAN METHOD; HYDROMETEOROLOGY; REGRESSION ANALYSIS; STREAMFLOW; SUSTAINABLE DEVELOPMENT; TIME SERIES; WATER MANAGEMENT;

UNITED STATES;

EID: 84893444157     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2014.01.023     Document Type: Article

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