Intelligent electronic nose systems for fire detection systems based on neural networks

Proceedings - The 2nd International Conference on Advanced Engineering Computing and Applications in Sciences, ADVCOMP 2008

Volumn , Issue , 2008, Pages 73-76

  Fujinaka, Toru ^a   Yoshioka, Michifumi ^a   Omatu, Sigeru ^a   Kosaka, Toshihisa ^b  

^a Osaka Prefecture University   (Japan)

^b GLORY LTD   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

ERROR BACK PROPAGATION; FIRE DETECTION SYSTEMS; HIGHLY-CORRELATED; INTELLIGENT ELECTRONICS; K-MEANS ALGORITHM; METAL OXIDE GAS SENSORS; TIME SERIES SIGNALS; TIME-SERIES DATA; TRAINING DATA SETS;

ARTIFICIAL INTELLIGENCE; ARTIFICIAL ORGANS; BACKPROPAGATION; COMPUTER AIDED ENGINEERING; COMPUTER SCIENCE; FIRE DETECTORS; METALLIC COMPOUNDS; SENSORS; SENSORY AIDS; TIME SERIES;

FIRES;

EID: 67650108610     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ADVCOMP.2008.47     Document Type: Conference Paper

References (4)

1. J. A. Milke, "Application of Neural Networks for discriminating Fire Detectors", International Conference on Automatic Fire Detection, AUBE'95, 10th, Duisburg, Germany, pp. 213-222, 1995.
2. B. Charumporn, M. Yoshioka, T. Fujinaka, and S. Omatu, "An Electronic Nose System Using Back Propagation Neural Networks with a Centroid Training Data Set", Proc. Eighth International Symposium on Artificial Life and Robotics, Japan, pp. 605-608, 2003.
3. General Information for TGS sensors, Figaro Engineering, available at www.figarosensor.com/products/general.pdf.
4. W. L. Carlson and B. Thorne, Applied Statistical Methods, Prentice Hall International, 1997.