Artificial intelligence-based inductive models for prediction and classification of fecal coliform in surface waters

Journal of Environmental Engineering

Volumn 134, Issue 9, 2008, Pages 789-799

  Tufail, Mohammad ^a,b   Ormsbee, Lindell ^c   Teegavarapu, Ramesh ^d  

^a UNIVERSITY OF ENGINEERING AND TECHNOLOGY   (Pakistan)

^b UNIVERSITY OF KENTUCKY   (United States)

^c UNIVERSITY OF KENTUCKY   (United States)

^d Florida Atlantic Univ   (United States)

Author keywords

Artificial intelligence; Computation; Neural networks; Pathogens; Predictions; Regression models; Surface waters; Watersheds

Indexed keywords

ARTIFICIAL NEURAL NETWORKS; ASSOCIATED WATER; COMPUTATION; DATA-DRIVEN MODELING; FECAL COLIFORM; FUNCTION APPROXIMATIONS; INDICATOR ORGANISMS; INDUCTIVE MODELING; PATHOGENS; PREDICTIONS; PROCESS-BASED MODELING; RAW DATA; REGRESSION MODELLING; REGRESSION MODELS; RELATIVE PERFORMANCE; SIMPLE REGRESSION MODELS; TECHNIQUES USED; WATERSHEDS;

APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE; CHLORINE COMPOUNDS; CLASSIFICATION (OF INFORMATION); CYBERNETICS; ELECTRIC FAULT LOCATION; FOOD PROCESSING; FORECASTING; GENETIC ALGORITHMS; LIGHTNING; NEURAL NETWORKS; OFFSHORE OIL WELL PRODUCTION; REGRESSION ANALYSIS; SURFACE WATERS; WATER POLLUTION; WATER QUALITY;

HYDRAULIC MODELS;

ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; BIOINDICATOR; COMPARATIVE STUDY; FECAL COLIFORM; GENETIC ALGORITHM; PATHOGEN; PREDICTION; REGRESSION ANALYSIS; SURFACE WATER; WATER QUALITY; WATERSHED;

EID: 49749090140     PISSN: 07339372     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)0733-9372(2008)134:9(789)     Document Type: Article

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