Title :
A Decision-Making Method for Fire Detection Data Fusion Based on Rough Set Approach
Author_Institution :
Sch. of Civil Aviation & Safety Eng., Shenyang Aerosp. Univ., Shenyang, China
Abstract :
This paper introduces an attribute reduction method based on the characteristics of consistent approximation space (CAS) of rough set. The proposed method can be used to fuse alarm signals from different kinds of fire sensors using decision rules derived from a sample data in CAS with the data classification features of CAS. The experiment results of an example data set show that this method can fuse different kinds of fire alarms to detect the occurrence of fire as well as the type of fires and give the confidence of the decisions.
Keywords :
decision making; fires; rough set theory; sensor fusion; signal detection; alarm signals; attribute reduction method; consistent approximation space; decision-making method; fire detection data fusion; fire sensors; rough set approach; Detectors; Fires; Fuses; Set theory; Temperature distribution; Temperature sensors; attribute reduction; consistent approximation space; fire detection; information fusion; rough set;
Conference_Titel :
Intelligent System Design and Engineering Application (ISDEA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-8333-4
DOI :
10.1109/ISDEA.2010.227
