Fuzzy self-organizing hybrid neural network for gas analysis system

Stanisław Osowski , Kazimierz Brudzewski

Abstract

The paper presents the gas analysis system applying the self-organizing fuzzy hybrid neural network. The network is composed of the self-organizing competitive fuzzy layer and the supervised multilayer perceptron (MLP) subnetwork, connected in cascade. The characteristic features of this network structure for gas analysis systems are discussed and the results of experiments compared to standard neural solutions based on MLP or classical hybrid network employing the Kohonen layer
Author Stanisław Osowski (FoEE / ITEEMIS)
Stanisław Osowski,,
- The Institute of the Theory of Electrical Engineering, Measurement and Information Systems
, Kazimierz Brudzewski (FC / CICSST)
Kazimierz Brudzewski,,
- Chair Of Inorganic Chemistry And Solid State Technology
Journal seriesIEEE Transactions On Instrumentation And Measurement, ISSN 0018-9456
Issue year2000
Vol49
No2
Pages424-428
Keywords in Englishair pollution measurement, array signal processing, cascade connected, chemical engineering computing, feature extraction, feedforward neural nets, fuzzy neural nets, fuzzy self-organizing hybrid neural network, gas analysis system, gas pollutants recognition, gas sensors, learning (artificial intelligence), learning patterns, mean absolute error, multilayer perceptrons, pattern clustering, self-organising feature maps, self-organizing competitive fuzzy layer, semiconductor oxide gas sensors, Sensor array, signal processing, supervised multilayer perceptron subnetwork
ASJC Classification2208 Electrical and Electronic Engineering; 3105 Instrumentation
DOIDOI:10.1109/19.843090
Score (nominal)25
Score sourcejournalList
Publication indicators Scopus Citations = 7; WoS Citations = 5; GS Citations = 12.0; Scopus SNIP (Source Normalised Impact per Paper): 2000 = 0.861; WoS Impact Factor: 2006 = 0.572 (2) - 2007=0.952 (5)
Citation count*12 (2016-07-08)
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* presented citation count is obtained through Internet information analysis and it is close to the number calculated by the Publish or Perish system.
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