Forecasting stream water temperature using regression analysis, artificial neural network, and chaotic non-linear dynamic models

Journal of Hydrology

Volumn 378, Issue 3-4, 2009, Pages 325-342

  Sahoo, G B ^a   Schladow, S G ^a   Reuter, J E ^a  

^a UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Back propagation neural network; Chaos algorithms; Genetic algorithms; Multiple regression analysis; Radial basic function neural network; Stream temperature

Indexed keywords

BACK PROPAGATION NEURAL NETWORK; CHAOS ALGORITHMS; MULTIPLE REGRESSION ANALYSIS; RADIAL BASIC FUNCTION NEURAL NETWORK; STREAM TEMPERATURE;

ATMOSPHERIC TEMPERATURE; BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; COMPUTATIONAL FLUID DYNAMICS; DIELECTRIC PROPERTIES; ELECTRIC LOAD FORECASTING; GENETIC ALGORITHMS; METAL ANALYSIS; NEURAL NETWORKS; OPTIMIZATION; PHASE SPACE METHODS; POWER SPECTRUM; REGRESSION ANALYSIS; RIVERS; SPECTRUM ANALYSIS; SPECTRUM ANALYZERS; SUN; TIME SERIES; WATER ANALYSIS;

TIME SERIES ANALYSIS;

AIR TEMPERATURE; ARTIFICIAL NEURAL NETWORK; BACK PROPAGATION; CHAOTIC DYNAMICS; DATA SET; EMPIRICAL ANALYSIS; FORECASTING METHOD; GENETIC ALGORITHM; NUMERICAL MODEL; PERFORMANCE ASSESSMENT; POPULATION DISTRIBUTION; REGRESSION ANALYSIS; SHORTWAVE RADIATION; SOLAR RADIATION; STREAMWATER; WATER POLLUTION; WATER TEMPERATURE;

EID: 70350495365     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2009.09.037     Document Type: Article

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