Structural repair prioritization of buildings damaged after earthquake using fuzzy logic model
© 2016, Fuji Technology Press. All rights reserved. Chiangrai is a city located in the seismic risk area. The recent earthquake with magnitude of 6.3 occurred on May 5, 2014 caused widespread damage to buildings. However, with limitation of engineers, equipment and budget, it is impossible to repair...
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th-cmuir.6653943832-423062017-09-28T04:26:19Z Structural repair prioritization of buildings damaged after earthquake using fuzzy logic model Saicheur K. Hansapinyo C. © 2016, Fuji Technology Press. All rights reserved. Chiangrai is a city located in the seismic risk area. The recent earthquake with magnitude of 6.3 occurred on May 5, 2014 caused widespread damage to buildings. However, with limitation of engineers, equipment and budget, it is impossible to repair all buildings in the same time. Therefore, this research proposes a method to identify critical buildings and prioritize their repairing requirements using fuzzy logic. The strength of fuzzy logic is that it can approximate the vague information, unable to make decision, to the numerical data. The evaluated factors were composed of building damaged level, indirect impact and building occupancy. With the vague information, the IFTHEN rule based form was adopted to evaluate an important index of each building. Results of the analysis was found that the buildings having more important, severely damaged and high indirect impacts on the community, such as hospital buildings and power plants will be considered with higher priority to repairs. The important indexes of the buildings were 0.718 and 0.500, respectively. For buildings with less important as garage buildings, the important index was 0.114 which identified as non-urgent repair. 2017-09-28T04:26:19Z 2017-09-28T04:26:19Z 2016-01-01 Journal 18812473 2-s2.0-84973548027 10.20965/jdr.2016.p0559 https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84973548027&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42306 |
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© 2016, Fuji Technology Press. All rights reserved. Chiangrai is a city located in the seismic risk area. The recent earthquake with magnitude of 6.3 occurred on May 5, 2014 caused widespread damage to buildings. However, with limitation of engineers, equipment and budget, it is impossible to repair all buildings in the same time. Therefore, this research proposes a method to identify critical buildings and prioritize their repairing requirements using fuzzy logic. The strength of fuzzy logic is that it can approximate the vague information, unable to make decision, to the numerical data. The evaluated factors were composed of building damaged level, indirect impact and building occupancy. With the vague information, the IFTHEN rule based form was adopted to evaluate an important index of each building. Results of the analysis was found that the buildings having more important, severely damaged and high indirect impacts on the community, such as hospital buildings and power plants will be considered with higher priority to repairs. The important indexes of the buildings were 0.718 and 0.500, respectively. For buildings with less important as garage buildings, the important index was 0.114 which identified as non-urgent repair. |
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Saicheur K. Hansapinyo C. |
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Saicheur K. Hansapinyo C. Structural repair prioritization of buildings damaged after earthquake using fuzzy logic model |
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Saicheur K. Hansapinyo C. |
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Saicheur K. |
title |
Structural repair prioritization of buildings damaged after earthquake using fuzzy logic model |
title_short |
Structural repair prioritization of buildings damaged after earthquake using fuzzy logic model |
title_full |
Structural repair prioritization of buildings damaged after earthquake using fuzzy logic model |
title_fullStr |
Structural repair prioritization of buildings damaged after earthquake using fuzzy logic model |
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Structural repair prioritization of buildings damaged after earthquake using fuzzy logic model |
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structural repair prioritization of buildings damaged after earthquake using fuzzy logic model |
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2017 |
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https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84973548027&origin=inward http://cmuir.cmu.ac.th/jspui/handle/6653943832/42306 |
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