کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
806369 1468263 2012 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Development of a localized probabilistic sensitivity method to determine random variable regional importance
کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی مکانیک
پیش نمایش صفحه اول مقاله
Development of a localized probabilistic sensitivity method to determine random variable regional importance
چکیده انگلیسی

There are many methods to identify the important variable out of a set of random variables, i.e., “inter-variable” importance; however, to date there are no comparable methods to identify the “region” of importance within a random variable, i.e., “intra-variable” importance. Knowledge of the critical region of an input random variable (tail, near-tail, and central region) can provide valuable information towards characterizing, understanding, and improving a model through additional modeling or testing. As a result, an intra-variable probabilistic sensitivity method was developed and demonstrated for independent random variables that computes the partial derivative of a probabilistic response with respect to a localized perturbation in the CDF values of each random variable. These sensitivities are then normalized in absolute value with respect to the largest sensitivity within a distribution to indicate the region of importance. The methodology is implemented using the Score Function kernel-based method such that existing samples can be used to compute sensitivities for negligible cost. Numerical examples demonstrate the accuracy of the method through comparisons with finite difference and numerical integration quadrature estimates.


► Probabilistic sensitivity methodology.
► Determines the “region” of importance within random variables such as left tail, near tail, center, right tail, etc.
► Uses the Score Function approach to reuse the samples, hence, negligible cost.
► No restrictions on the random variable types or limit states.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Reliability Engineering & System Safety - Volume 107, November 2012, Pages 3–15
نویسندگان
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