摘要
为解决传统火灾报警系统在应对地铁火灾报警时存在的即时性差、灵敏度及智能化水平低等问题,基于Fuzzy ARTMAP网络,结合Yu范数相似度准则与软竞争学习机制,提出1种软竞争学习Fuzzy ARTMAP算法,弥补传统Fuzzy ARTMAP网络胜者为王规则导致的区域重叠而产生误判的不足;结合地铁光纤光栅传感网络数据,将该算法应用于地铁火灾识别。结果表明:与传统的Fuzzy ARTMAP相比,该算法可快速有效地识别地铁火灾趋势,为地铁火灾识别系统研究提供理论支持。
In order to overcome the problems of poor instantaneity,low sensitivity and low level of intelligence when coping with the subway fire alarm by using the traditional fire alarm system,a soft competitive learning Fuzzy ARTMAP(Soft Fuzzy ARTMAP)algorithm was proposed based on the fuzzy ARTMAP network combining with the similarity criterion of Yu norm and the soft competitive learning mechanism,and it maked up the shortcoming of the traditional Fuzzy ARTMAP network that the rule of“winner-take-all”caused the area overlap,which led to the misjudge.Combined with the data of subway FBG sensing network,the algorithm was applied in the subway fire detection.The results showed that compared with the traditional Fuzzy ARTMAP,the algorithm could identify the subway fire trend quickly and effectively,and provide theoretical support for the research of subway fire detection system.
作者
徐一旻
王世琪
吕伟
霍非舟
李墨潇
XU Yimin;WANG Shiqi;LYU Wei;HUO Feizhou;LI Moxiao(School of Safety Science and Emergency Management,Wuhan University of Technology,Wuhan Hubei 430070,China;National Engineering Laboratory for Fiber Optic Sensing Technology,Wuhan University of Technology,Wuhan Hubei 430070,China)
出处
《中国安全生产科学技术》
CAS
CSCD
北大核心
2020年第9期50-56,共7页
Journal of Safety Science and Technology
基金
“十三五”国家重点研发计划项目(2018YFC0807000)
中国博士后科学基金项目(2018M632937)
中央高校基本科研业务费项目(2019IVA075,2019III168CG)。
