A modular neural architecture for bathythermograms classification

Author

Stéphan, Y. ; Frachon, B.

Author_Institution

Centre Mil. d´´Oceanogr., Brest, France

fYear

1993

fDate

18-21 Oct 1993

Abstract

Presents a neural approach for bathythermogram classification. A modular architecture of multi-layer perceptrons (MLP) stemming from a preclassification into five main types of temperature profile is used. The types and classes are issued from a pre-established typology. The performance of this approach is evaluated on a Red Sea profiles database. The results show that the method is efficient but suffers from classes overlapping

Keywords

feedforward neural nets; oceanographic techniques; pattern recognition; temperature measurement; XBT; bathythermogram; bathythermograph; class overlapping; data classification; feedforward neural net; geophysics computing; measurement technique; method; modular neural architecture; multi-layer perceptron; neural net; neural network; ocean temperature; preclassification; sea; thermal structure; vertical profile; Area measurement; Databases; Extraterrestrial measurements; Marine vehicles; Multilayer perceptrons; Ocean temperature; Oceanographic techniques; Sea measurements; Statistics; Time measurement;

fLanguage

English

Publisher

ieee

Conference_Titel

OCEANS '93. Engineering in Harmony with Ocean. Proceedings

Conference_Location

Victoria, BC

Print_ISBN

0-7803-1385-2

Type

conf

DOI

10.1109/OCEANS.1993.325963

Filename

325963

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=2115842