Suspended sediment modeling using genetic programming and soft computing techniques

Journal of Hydrology

Volumn 450-451, Issue , 2012, Pages 48-58

  Kisi, Ozgur ^a   Dailr, Ali Hosseinzadeh ^b   Cimen, Mesut ^c   Shiri, Jalal ^b  

^a CANIK BASARI UNIVERSITY   (Turkey)

^b UNIVERSITY OF TABRIZ   (Iran)

^c SULEYMAN DEMIREL UNIVERSITY   (Turkey)

Author keywords

Artificial intelligence; Estimating; Sediment load; Sensitivity analysis

Indexed keywords

ADAPTIVE NEURO-FUZZY INFERENCE SYSTEM; COEFFICIENT OF DETERMINATION; COMPARISON RESULT; ESTIMATING; MEAN ABSOLUTE ERROR; OPERATOR FUNCTION; OPTIMAL FITNESS; RESIDUAL MASS; SEDIMENT LOADS; SOFTCOMPUTING TECHNIQUES; SUSPENDED SEDIMENT LOADS; SVM MODEL;

ARTIFICIAL INTELLIGENCE; ESTIMATION; GENETIC PROGRAMMING; LEARNING ALGORITHMS; NEURAL NETWORKS; SEDIMENTOLOGY; SENSITIVITY ANALYSIS; SOFT COMPUTING; SUPPORT VECTOR MACHINES; WATER MANAGEMENT;

SUSPENDED SEDIMENTS;

ALGORITHM; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; COMPUTER SIMULATION; ENGINEERING; ESTIMATION METHOD; HYDROLOGICAL MODELING; NUMERICAL MODEL; SENSITIVITY ANALYSIS; SUSPENDED SEDIMENT; WATER MANAGEMENT; WATER RESOURCE;

CUMBERLAND RIVER; UNITED STATES;

EID: 84862679428     PISSN: 00221694     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jhydrol.2012.05.031     Document Type: Article

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