DocumentCode
130995
Title
A spatial awareness case-based reasoning approach for typhoon disaster management
Author
Xi Zhou ; Fei Wang
Author_Institution
Grad. Sch. at Shenzhen, Tsinghua Univ., Shenzhen, China
fYear
2014
fDate
27-29 June 2014
Firstpage
893
Lastpage
896
Abstract
Knowledge learning from similar historical cases is critical for emergency decision making against typhoons. Case-based reasoning technology is increasingly adopted to find the appropriate disaster cases matched to current typhoons. However, the matching results is not satisfying. The reasons are that the typhoon disaster case repository is lacking in a unified and comprehensive specification and that the important spatial attributes of cases are often overlooked or simply described. Based on the investigation of practical typhoon cases, a novel approach is proposed to define the case with explicit and comprehensive spatial multi-elements. With the spatial analysis function and the data management capabilities of GIS, the spatial awareness CBR method is discussed. Lastly, a framework of applying the prosed method to Guangdong Emergency Platform System for testifying is introduced.
Keywords
case-based reasoning; decision making; emergency management; geographic information systems; learning (artificial intelligence); storms; GIS; Guangdong emergency platform system; comprehensive spatial multi-elements; data management capabilities; disaster cases; emergency decision making; explicit spatial multi-elements; knowledge learning; spatial analysis function; spatial awareness CBR method; spatial awareness case-based reasoning approach; typhoon disaster case repository; typhoon disaster management; Cognition; Disaster management; Floods; Geographic information systems; Sociology; Statistics; Tropical cyclones; Case-based reasoning (CBR); GIS; spatial awareness; typhoon disaster management;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location
Beijing
ISSN
2327-0586
Print_ISBN
978-1-4799-3278-8
Type
conf
DOI
10.1109/ICSESS.2014.6933709
Filename
6933709
Link To Document