- 【Updated on May 12, 2025】 Integration of CiNii Dissertations and CiNii Books into CiNii Research
- Trial version of CiNii Research Knowledge Graph Search feature is available on CiNii Labs
- Suspension and deletion of data provided by Nikkei BP
- Regarding the recording of “Research Data” and “Evidence Data”
Acquisition of fuzzy rules for fire judgment system
Description
Recently, every building has fire alarm systems to detect a fire in its early stages and not to spread the damage of the fire. These systems are essential to protect human lives and properties. However, the lack of reliability in these systems, in which false alarms have arisen many times, has been a serious problem. This paper proposes a new intelligent fire judgment system with feature extraction from time series of smoke density using fuzzy rules acquired by Genetic Algorithm (GA). The GA in this paper uses selective elements method for rule generation. This system shows high reliability for the fire alarm systems through computer experiments. This paper also shows that effective features as fuzzy rules for each category scan be extracted using this method.
Journal
-
- Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694)
-
Proceedings 2003 IEEE International Symposium on Computational Intelligence in Robotics and Automation. Computational Intelligence in Robotics and Automation for the New Millennium (Cat. No.03EX694) 2 653-657, 2004-03-01
IEEE
