A GIS-based multi-criteria seismic vulnerability assessment using the integration of granular computing rule extraction and artificial neural networks

2017 ◽  
Vol 21 (6) ◽  
pp. 1237-1259 ◽  
Author(s):  
Hossein Sheikhian ◽  
Mahmoud Reza Delavar ◽  
Alfred Stein
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Vulnerability Assessment ◽  
Granular Computing ◽  
Seismic Vulnerability ◽  
Rule Extraction ◽  
Seismic Vulnerability Assessment ◽  
Artificial Neural

scholarly journals PHYSICAL SEISMIC VULNERABILITY ASSESSMENT OF TEHRAN USING THE INTEGRATION OF GRANULAR COMPUTING AND INTERVAL DEMPSTER- SHAFER

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 469-477
Author(s):  
M. R. Delavar ◽  
M. Bahrami ◽  
M. Zare
Keyword(s):  
Vulnerability Assessment ◽  
Granular Computing ◽  
Seismic Vulnerability ◽  
Interval Computation ◽  
Combination Rule ◽  
Effective Parameters ◽  
Physical Vulnerability ◽  
Seismic Vulnerability Assessment ◽  
Vulnerability Map

Several faults exist in the vicinity of Tehran, the capital of Iran such as North Tehran, Ray, Mosha and Kahrizak. One way to assist reducing the damage caused by the earthquake is the production of a seismic vulnerability map. The study area in this research is Tehran, based on the assumption of the activation of North Tehran fault. Degree of Physical seismic vulnerability caused by the earthquake depends on a number of criteria. In this study the intensity of the earthquake, land slope, numbers of buildings’ floors as well as their materials are considered as the effective parameters. Hence, the production of the seismic vulnerability map is a multi criteria issue. In this problem, the main source of uncertainty is related to the experts’ opinions regarding the seismic vulnerability of Tehran statistical units. The main objectives of this study are to exploit opinions of the experts, undertaking interval computation and interval Dempster-Shafer combination rule to reduce the uncertainty in the opinions of the experts and customizing granular computing to extract the rules and to produce Tehran physical seismic vulnerability map with a higher confidence. Among 3174 statistical units of Tehran, 150 units were randomly selected and using interval computation, their physical vulnerabilities were determined by the experts in earthquake-related fields. After the fusion of the experts’ opinions using interval Dempster-Shafer, the information table is prepared as the input to granular computing and then rules are extracted with minimum inconsistency. Finally, the seismic physical vulnerability map of Tehran was produced with % 72 accuracy.

Sign in / Sign up

Export Citation Format

Share Document