A data-driven approach to predict suspended-sediment reference concentration under non-breaking waves

Continental Shelf Research

Volumn 46, Issue , 2012, Pages 96-106

  Oehler, Francois ^a   Coco, Giovanni ^a   Green, Malcolm O ^a   Bryan, Karin R ^b  

^a NATIONAL INSTITUTE OF WATER AND ATMOSPHERIC RESEARCH   (New Zealand)

^b UNIVERSITY OF WAIKATO   (New Zealand)

Author keywords

Acoustic backscatter sensors; Artificial Neural Networks; Bed sediment grainsize; Boosted Regression Trees; Non breaking waves; Wave orbital semi excursion

Indexed keywords

ALGORITHM; ARTIFICIAL NEURAL NETWORK; BACKSCATTER; BEDLOAD; BREAKING WAVE; CONCENTRATION (COMPOSITION); DATA SET; GRAIN SIZE; HYDRODYNAMICS; MEASUREMENT METHOD; MORPHODYNAMICS; NUMERICAL MODEL; REGRESSION ANALYSIS; SEDIMENT ANALYSIS; SENSOR; SUSPENDED SEDIMENT; WATER DEPTH;

EID: 84865774272     PISSN: 02784343     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.csr.2011.01.015     Document Type: Article

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