Determination of the optimal parameters in regression models for the prediction of chlorophyll-a: A case study of the Yeongsan Reservoir, Korea

Science of the Total Environment

Volumn 407, Issue 8, 2009, Pages 2536-2545

  Cho, Kyung Hwa ^a   Kang, Joo Hyon ^a   Ki, Seo Jin ^a   Park, Yongeun ^a   Cha, Sung Min ^a   Kim, Joon Ha ^a  

^a Gwangju Institute of Science and Technology (GIST)   (South Korea)

Author keywords

Chlorophyll a Prediction; F overall statistics; Multiple Linear Regression (MLR); Optimal parameters; Principal Component Regression (PCR); Uncertainty

Indexed keywords

CHLOROPHYLL-A PREDICTION; F-OVERALL STATISTICS; MULTIPLE LINEAR REGRESSION (MLR); OPTIMAL PARAMETERS; PRINCIPAL COMPONENT REGRESSION (PCR); UNCERTAINTY;

BIOCHEMICAL OXYGEN DEMAND; CHLOROPHYLL; COLIFORM BACTERIA; COSMIC RAYS; DISSOLUTION; DISSOLVED OXYGEN; HYDRAULIC MODELS; INDICATORS (CHEMICAL); NONMETALS; OPTIMIZATION; PARAMETER ESTIMATION; PORPHYRINS; RESERVOIRS (WATER); RESOURCE ALLOCATION; WATER MANAGEMENT; WATER POLLUTION; WATER QUALITY;

REGRESSION ANALYSIS;

BIOCHEMICAL OXYGEN DEMAND; CHEMICAL OXYGEN DEMAND; CHLOROPHYLL A; CONCENTRATION (COMPOSITION); ERROR ANALYSIS; MODEL VALIDATION; PREDICTION; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; WATER QUALITY;

CHLOROPHYLL; FRESH WATER; KOREA; LINEAR MODELS; PRINCIPAL COMPONENT ANALYSIS; REGRESSION ANALYSIS; REPRODUCIBILITY OF RESULTS;

ASIA; EURASIA; FAR EAST; KOREA; SOUTH CHOLLA; SOUTH KOREA; YEONGSAN RESERVOIR;

EID: 61649121876     PISSN: 00489697     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.scitotenv.2009.01.017     Document Type: Article

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