Uncertainty Management in Seismic Vulnerability Assessment Using Granular Computing Based on Neighborhood Systems

2015 ◽  
pp. 269-282
Keyword(s):  
Vulnerability Assessment ◽  
Granular Computing ◽  
Seismic Vulnerability ◽  
Uncertainty Management ◽  
Seismic Vulnerability Assessment

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.

scholarly journals INTEGRATED ESTIMATION OF SEISMIC PHYSICAL VULNERABILITY OF TEHRAN USING RULE BASED GRANULAR COMPUTING

2015 ◽  
Vol XL-3/W3 ◽  
pp. 187-193 ◽  
Author(s):  
H. Sheikhian ◽  
M. R. Delavar ◽  
A. Stein
Keyword(s):  
Vulnerability Assessment ◽  
Granular Computing ◽  
Seismic Vulnerability ◽  
Seismic Intensity ◽  
Effective Parameters ◽  
Physical Vulnerability ◽  
Physical Damage ◽  
Seismic Vulnerability Assessment ◽  
The North ◽  
Prone Area

Tehran, the capital of Iran, is surrounded by the North Tehran fault, the Mosha fault and the Rey fault. This exposes the city to possibly huge earthquakes followed by dramatic human loss and physical damage, in particular as it contains a large number of non-standard constructions and aged buildings. Estimation of the likely consequences of an earthquake facilitates mitigation of these losses. Mitigation of the earthquake fatalities may be achieved by promoting awareness of earthquake vulnerability and implementation of seismic vulnerability reduction measures. In this research, granular computing using generality and absolute support for rule extraction is applied. It uses coverage and entropy for rule prioritization. These rules are combined to form a granule tree that shows the order and relation of the extracted rules. In this way the seismic physical vulnerability is assessed, integrating the effects of the three major known faults. Effective parameters considered in the physical seismic vulnerability assessment are slope, seismic intensity, height and age of the buildings. Experts were asked to predict seismic vulnerability for 100 randomly selected samples among more than 3000 statistical units in Tehran. The integrated experts’ point of views serve as input into granular computing. Non-redundant covering rules preserve the consistency in the model, which resulted in 84% accuracy in the seismic vulnerability assessment based on the validation of the predicted test data against expected vulnerability degree. The study concluded that granular computing is a useful method to assess the effects of earthquakes in an earthquake prone area.

A Bayesian approach to rapid seismic vulnerability assessment at urban scale

2017 ◽  
Vol 12 (1) ◽  
pp. 36-46 ◽  
Author(s):  
Gian Paolo Campostrini ◽  
Sabrina Taffarel ◽  
Giulia Bettiol ◽  
Maria Rosa Valluzzi ◽  
Francesca Da Porto ◽  
...  
Keyword(s):  
Bayesian Approach ◽  
Vulnerability Assessment ◽  
Seismic Vulnerability ◽  
Seismic Vulnerability Assessment
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