International Journal of Optimization in Civil Engineering
دانشگاه علم و صنعت ایران
Iran University of Science & Technology
http://ijoce.iust.ac.ir
18
agent2
2228-7558
en
jalali
1397
7
1
gregorian
2018
10
1
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online
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fulltext
en
AN OPTIMUM APPROACH TOWARDS SEISMIC FRAGILITY FUNCTION OF STRUCTURES THROUGH METAHEURISTIC HARMONY SEARCH ALGORITHM
Optimal analysis
Optimal analysis
پژوهشي
Research
Vulnerability assessment of structures encounter many uncertainties like seismic excitations intensity and response of structures. The most common approach adopted to deal with these uncertainties is vulnerability assessment through fragility functions. Fragility functions exhibit the probability of exceeding a state namely performance-level as a function of seismic intensity. A common approach is finding some response points of the fragility function and then fitting a typical probability distribution like lognormal through curve fitting estimation techniques. Maximum-likelihood approach is a fitting method to find the probability distribution parameters. Performing this approach for distributions like lognormal which is defined by just two parameters are straight forward while for more complicated distribution which are based on additional characterizing parameters is not feasible, since this approach is based on minimizing an error function through classic mathematical approaches like calculating partial derivations. An applicable modification is to add an efficient optimization approach to determine maximum-likelihood function. In this article, an optimization algorithm is proposed with maximum-likelihood-estimation and the results indicate the efficiency and feasibility of future developments in finding the most appropriate fragility function.
optimization, harmony search algorithm, vulnerability assessment, fragility function, maximum likelihood estimation.
587
600
http://ijoce.iust.ac.ir/browse.php?a_code=A-10-66-202&slc_lang=en&sid=en
S.
Dehghani Fordoei
`180031947532846001346`

180031947532846001346
No
S.A.
Razavian Amrei
`180031947532846001347`

180031947532846001347
Yes
M.
Eghbali
`180031947532846001348`

180031947532846001348
No
M. Sh.
Nasrollah Beigi
`180031947532846001349`

180031947532846001349
No