Prediction of coarse particle movement with adaptive neuro-fuzzy inference systems

Hydrological Processes

Volumn 25, Issue 22, 2011, Pages 3513-3524

  Valyrakis, Manousos ^a   Diplas, Panayiotis ^a   Dancey, Clint L ^a  

^a VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

Author keywords

ANFIS; Forecasting; Grain entrainment; Wavelet transform

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; ANFIS; ANFIS MODEL; COARSE PARTICLES; COMPLEX DYNAMICS; ENERGY CONTENT; FLOW CONDITION; FLUME EXPERIMENT; FORECAST ACCURACY; FORECASTING PROCEDURES; HE-NE LASERS; HYDRODYNAMIC FORCING; INPUT AND OUTPUTS; INPUT SIGNAL; LEARNING AND ADAPTATION; MODEL COMPONENTS; NEURO-FUZZY APPROACH; PARTICLE DISPLACEMENT; PARTICLE RESPONSE; PERFORMANCE INDICES; SOLID PARTICLES; STREAMWISE VELOCITY; TIME AND FREQUENCY DOMAINS; TIME HISTORY; TRAINING AND TESTING; TRIAL-AND-ERROR APPROACH;

DOPPLER EFFECT; FORECASTING; FUZZY NEURAL NETWORKS; FUZZY SYSTEMS; LASER DOPPLER VELOCIMETERS; OPTOELECTRONIC DEVICES; TRACKING (POSITION); TURBULENT FLOW; WAVELET TRANSFORMS;

FUZZY INFERENCE;

ARTIFICIAL NEURAL NETWORK; ENTRAINMENT; FLOW VELOCITY; FORECASTING METHOD; FUZZY MATHEMATICS; GRAIN SIZE; HYDRODYNAMIC FORCE; NONLINEARITY; PARTICLE MOTION; PREDICTION; TURBULENT FLOW; WAVELET ANALYSIS;

EID: 80053920081     PISSN: 08856087     EISSN: 10991085     Source Type: Journal    
DOI: 10.1002/hyp.8228     Document Type: Article

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