A support vector regression-firefly algorithm-based model for limiting velocity prediction in sewer pipes

Water Science and Technology

Volumn 73, Issue 9, 2016, Pages 2244-2250

  Ebtehaj, Isa ^a   Bonakdari, Hossein ^a  

^a RAZI UNIVERSITY   (Iran)

Author keywords

Bed load; Firefly algorithm (FFA); Pipe; Sediment transport; Sewer; Support vector regression (SVR)

Indexed keywords

ALGORITHMS; BIOLUMINESCENCE; GENETIC ALGORITHMS; GENETIC PROGRAMMING; HYDRAULIC MACHINERY; MEAN SQUARE ERROR; NEURAL NETWORKS; OPTIMIZATION; PIPE; REGRESSION ANALYSIS; SEDIMENT TRANSPORT; SEDIMENTATION; SEDIMENTS; SEWERS; SUPPORT VECTOR MACHINES; VECTORS;

BED LOAD; DENSIMETRIC FROUDE NUMBER; DIMENSIONLESS VARIABLES; ESSENTIAL CONSIDERATIONS; FIREFLY ALGORITHMS; MEAN ABSOLUTE PERCENTAGE ERROR; SUPPORT VECTOR REGRESSION (SVR); VOLUMETRIC CONCENTRATIONS;

FLOOD CONTROL;

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BEDLOAD; FRICTION; FROUDE NUMBER; NUMERICAL MODEL; PIPE; REGRESSION ANALYSIS; SEDIMENT TRANSPORT; SEWER NETWORK; SUPPORT VECTOR MACHINE; VELOCITY;

ARTIFICIAL NEURAL NETWORK; CALCULATION; FIREFLY; FRICTION; GENETIC MODEL; PREDICTION; SEDIMENT TRANSPORT; SEWER; STATISTICAL MODEL; SUPPORT VECTOR MACHINE; VELOCITY; ALGORITHM; ANIMAL; SANITATION; THEORETICAL MODEL; WATER FLOW;

ALGORITHMS; ANIMALS; MODELS, THEORETICAL; NEURAL NETWORKS (COMPUTER); SANITARY ENGINEERING; SUPPORT VECTOR MACHINE; WATER MOVEMENTS;

EID: 84968583582     PISSN: 02731223     EISSN: None     Source Type: Journal    
DOI: 10.2166/wst.2016.064     Document Type: Article

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