Application of artificial neural networks to the forecasting of dissolved oxygen content in the Hungarian section of the river Danube

Ecological Engineering

Volumn 100, Issue , 2017, Pages 63-72

  Csábrági, Anita ^a   Molnár, Sándor ^a   Tanos, Péter ^a   Kovács, József ^b  

^a SZENT ISTVÁN UNIVERSITY   (Hungary)

^b EÖTVÖS LORÁND UNIVERSITY   (Hungary)

Author keywords

Dissolved oxygen forecasting; General regression neural networks; Multilayer perceptron neural networks; Multivariate linear regression; Radial basis function neural network

Indexed keywords

DISSOLUTION; FORECASTING; FUNCTIONS; IMPORTANCE SAMPLING; INTELLIGENT SYSTEMS; LINEAR REGRESSION; MEAN SQUARE ERROR; MULTILAYER NEURAL NETWORKS; MULTILAYERS; NEURAL NETWORKS; NONLINEAR SYSTEMS; OXYGEN; RADIAL BASIS FUNCTION NETWORKS; REGRESSION ANALYSIS; RIVERS; SENSITIVITY ANALYSIS; SURFACE WATERS; WATER QUALITY;

COEFFICIENT OF DETERMINATION; DISSOLVED OXYGEN CONCENTRATIONS; EVALUATING MODEL PERFORMANCE; GENERAL REGRESSION NEURAL NETWORK; MULTI-LAYER PERCEPTRON NEURAL NETWORKS; MULTIVARIATE LINEAR REGRESSION MODEL; MULTIVARIATE LINEAR REGRESSIONS; RADIAL BASIS FUNCTION NEURAL NETWORKS;

DISSOLVED OXYGEN;

ARTIFICIAL NEURAL NETWORK; CONCENTRATION (COMPOSITION); DISSOLVED OXYGEN; ELECTRICAL CONDUCTIVITY; FORECASTING METHOD; GROUNDWATER; MULTIVARIATE ANALYSIS; PERFORMANCE ASSESSMENT; REGRESSION ANALYSIS; RIVER WATER; SENSITIVITY ANALYSIS; SURFACE WATER; WATER QUALITY;

DANUBE RIVER; HUNGARY;

EID: 85007228134     PISSN: 09258574     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecoleng.2016.12.027     Document Type: Article

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