کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4963967 | 1447417 | 2017 | 56 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Bayesian sparse polynomial chaos expansion for global sensitivity analysis
ترجمه فارسی عنوان
گسترش بی نظمی هرج و مرج بیزی برای تحلیل حساسیت جهانی
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نرم افزارهای علوم کامپیوتر
چکیده انگلیسی
Polynomial chaos expansions are frequently used by engineers and modellers for uncertainty and sensitivity analyses of computer models. They allow representing the input/output relations of computer models. Usually only a few terms are really relevant in such a representation. It is a challenge to infer the best sparse polynomial chaos expansion of a given model input/output data set. In the present article, sparse polynomial chaos expansions are investigated for global sensitivity analysis of computer model responses. A new Bayesian approach is proposed to perform this task, based on the Kashyap information criterion for model selection. The efficiency of the proposed algorithm is assessed on several benchmarks before applying the algorithm to identify the most relevant inputs of a double-diffusive convection model.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 318, 1 May 2017, Pages 474-496
Journal: Computer Methods in Applied Mechanics and Engineering - Volume 318, 1 May 2017, Pages 474-496
نویسندگان
Qian Shao, Anis Younes, Marwan Fahs, Thierry A. Mara,