Linear and non-linear T-S models for the eastern North Atlantic from Argo data: Role of surface salinity observations

Deep-Sea Research Part I: Oceanographic Research Papers

Volumn 56, Issue 10, 2009, Pages 1605-1614

  Ballabrera Poy, Joaquim ^a   Mourre, Baptiste ^a   Garcia Ladona, Emilio ^a   Turiel, Antonio ^a   Font, Jordi ^a  

^a INSTITUT DE CIÈNCIES DEL MAR   (Spain)

Author keywords

Argo; Atlantic Ocean; Neural networks; Regression analysis; Salinity; Temperature

Indexed keywords

ARGO; ATLANTIC OCEAN; DATA SETS; DATA SUBSETS; EARLY STOPPING; EMPIRICAL MODEL; HIDDEN LAYERS; INITIAL WEIGHTS; LOCAL MINIMUMS; NETWORK COMMITTEE; NON-LINEAR; NON-LINEAR MODEL; NON-LINEAR REGRESSION; NORTH ATLANTIC; NORTH ATLANTIC OCEAN; OVERFITTING; POLYNOMIAL MODELS; POTENTIAL APPLICATIONS; RANDOMLY DISTRIBUTED; SALINITY; SATELLITE MISSION; SURFACE SALINITIES; T S MODELS; TEMPERATURE PROFILES; TEST DATA; TRAINING DATA; VALIDATION DATA; VERTICAL SALINITY PROFILE; WATER MASS;

LINEAR REGRESSION; NEURAL NETWORKS; OCEANOGRAPHY; SALINITY MEASUREMENT; SULFUR COMPOUNDS;

HYDROGRAPHIC SURVEYS;

ARTIFICIAL NEURAL NETWORK; MODEL VALIDATION; REGRESSION ANALYSIS; SATELLITE IMAGERY; SEA SURFACE SALINITY; SEA SURFACE TEMPERATURE; TEMPERATURE PROFILE; WATER MASS;

ATLANTIC OCEAN; ATLANTIC OCEAN (NORTHEAST);

EID: 67949103525     PISSN: 09670637     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.dsr.2009.05.017     Document Type: Article

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