Development of a neural-based forecasting tool to classify recreational water quality using fecal indicator organisms

Water Research

Volumn 46, Issue 14, 2012, Pages 4508-4520

  Motamarri, Srinivas ^a   Boccelli, Dominic L ^a  

^a UNIVERSITY OF CINCINNATI   (United States)

Author keywords

Artificial neural network; Classification; Fecal coliform; Learning vector quantization; Linear regression; Surface water

Indexed keywords

ESCHERICHIA COLI; SURFACE WATERS; VECTOR QUANTIZATION; WATER QUALITY;

EXPLANATORY VARIABLES; FALSE NEGATIVE RATE; FECAL COLIFORM; FORECASTING TOOLS; INPUT SELECTION; LEARNING VECTOR QUANTIZATION; MODEL DEVELOPMENT; MULTIVARIATE LINEAR REGRESSIONS; NEURAL BASED FORECASTING; RECREATIONAL WATER QUALITY;

NEURAL NETWORKS;

RAIN;

ARTIFICIAL NEURAL NETWORK; BIOINDICATOR; CONCENTRATION (COMPOSITION); FECAL COLIFORM; FORECASTING METHOD; NUMERICAL MODEL; PATHOGENICITY; POLLUTANT SOURCE; RAINFALL; SURFACE WATER; WATER QUALITY;

ARTICLE; ARTIFICIAL NEURAL NETWORK; CONTROLLED STUDY; FALSE NEGATIVE RESULT; FECAL COLIFORM; FORECASTING; INDICATOR ORGANISM; INTERMETHOD COMPARISON; LEARNING VECTOR QUANTIZATION; MACHINE LEARNING; MULTIPLE LINEAR REGRESSION ANALYSIS; PRIORITY JOURNAL; UNITED STATES; WATER POLLUTION INDICATOR; WATER QUALITY;

CHARLES BASIN; MASSACHUSETTS; UNITED STATES;

ESCHERICHIA COLI;

EID: 84863541341     PISSN: 00431354     EISSN: 18792448     Source Type: Journal    
DOI: 10.1016/j.watres.2012.05.023     Document Type: Article

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