Coastal 'Big Data' and nature-inspired computation: Prediction potentials, uncertainties, and knowledge derivation of neural networks for an algal metric

Estuarine, Coastal and Shelf Science

Volumn 125, Issue , 2013, Pages 57-67

  Millie, David F ^a,b   Weckman, Gary R ^c   Young, William A ^d   Ivey, James E ^e   Fries, David P ^f   Ardjmand, Ehsan ^c   Fahnenstiel, Gary L ^b  

^a Palm Island Enviro Informatics LLC   (United States)

^b MICHIGAN TECHNOLOGICAL UNIVERSITY   (United States)

^c US Institute of Navigation   (United States)

^d OHIO UNIVERSITY   (United States)

^e FISH AND WILDLIFE RESEARCH INSTITUTE   (United States)

^f UNIVERSITY OF SOUTH FLORIDA   (United States)

Author keywords

Artificial neural networks; Decision trees; Empirical models; Environmental informatics; In situ chlorophyll; Sarasota Bay

Indexed keywords

ACCURACY ASSESSMENT; ALGA; ALGORITHM; ARTIFICIAL NEURAL NETWORK; CHLOROPHYLL; DATA ACQUISITION; DATA SET; DATABASE; DECISION ANALYSIS; EMPIRICAL ANALYSIS; ENVIRONMENTAL MONITORING; IN SITU MEASUREMENT; PREDICTION; SALINITY; SENSOR; TURBIDITY; UNCERTAINTY ANALYSIS; WATER TEMPERATURE;

FLORIDA [UNITED STATES]; SARASOTA BAY; UNITED STATES;

ALGAE;

EID: 84892440534     PISSN: 02727714     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ecss.2013.04.001     Document Type: Article

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