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Wieloczęstotliwościowe wieloetapowe klasyfikatory neuronowo-rozmyte do rozpoznawania typu dna morskiego

Treść / Zawartość
Identyfikatory
Warianty tytułu
Konferencja
17 th Symposium on Hydroacoustics (23-26.05.2000; Jurata; Polska)
Języki publikacji
PL
Abstrakty
EN
A hybrid multistage neuro-fuzzy classifiers were developedfor sea-bottom recognition from aeoustie eehoes. A multistage fuzry neural network was implemented and tested on the data eolleeted on two eehosounder's frequencies. Two struetures termed as incremental fuzz» neural network (IFNN) and aggregated fuzzy neural network (AFNN), were analysed. In IFNN, an approximate decision is undertaken firstly, based only on the one set of input variables. The decision is then fine-tuned by eonsidering more faetors in following stages until the final decision, assigning the output class, is undertaken. In AFNN, the input variables are divided into M subsets, where eaeh of them isfed to one sub-stage. The fina l output is derived by the reasoning with alt intermediate variables, which work as the outputs of substages in the preeeding stage. The proposed structures improve the generalisation ability of the system and reduees requirements on computation power and memory.
Słowa kluczowe
Czasopismo
Rocznik
Tom
Strony
39--44
Opis fizyczny
Bibliogr. 5 poz., rys.
Twórcy
autor
  • Politechnika Gdańska, Katedra Telemonitoringu Środowiska ul. Narutowicza 11/12, 80-952 Gdańsk
  • Politechnika Gdańska, Katedra Telemonitoringu Środowiska ul. Narutowicza 11/12, 80-952 Gdańsk
Bibliografia
  • [1] Stepnowski A., Moszyński M., Bakiera D., Komendarczyk R., Burczyński J., Visual Real-time Bottom Typing System and Neural Network Experiment for Seabed Classification, Proceedings of 3nd European Conference on Underwater Acoustics, Heraklion, 869-875, 1996.
  • [2] Maciołowska J., Stepnowski A., Tran. V. D., Fish Schools and Seabed Identification Using Neural Networks and Fuzzy Logic Classifiers, Proceedings of the Fourth European Conjerence on Underwater Acoustics, Rome, 275-280,1998.
  • [3] Stepnowski A., Maciołowska J., Tran V. D., Bottom type identification using combined neuro-fuzzy classifier operating on multi-frequency data, Archives of Acoustic, 24 (3), 365-378,1999.
  • [4] Jang, 1. S. R. and Sun, C. T. and Mizutani, E., Neuro-Fuzzy and Soft Computing - A Computational Approach to Learning and Machine Intelligence, Prentice-Hall International, Inc., 1997
  • [5] Dung T. V. Maciołowska 1., Stepnowski A., Sea Bottom Typing Using Neuro-Fuzzy Classifier Operating on Multi-Frequency Data, Proceedings of the 2 nd EAA International Symposium on Hydroacoustics, Gdańsk-Jurata, 79-84, 1999.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-40859de7-b13b-4c20-843b-9a7ee916f8d8
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