利用新型自适应线性取样法对多重重要性取样中心进行全局敏感性分析

IF 2.2 3区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

Engineering Optimization Pub Date : 2024-07-04 DOI:10.1080/0305215x.2024.2366489

Xin Fan, Yongshou Liu

引用次数: 0

摘要

为了更有效地解决工程中的可靠性分析问题，必须改进线采样 (LS) 方法，该方法通常对罕见事件有效。本论文的目的是...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Global sensitivity analysis for multiple importance sampling centres using a novel adaptive line sampling method

To achieve more efficient resolution of reliability analysis problems in engineering, it is essential to enhance the line sampling (LS) method, which is typically effective for rare events. This ar...

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来源期刊

Engineering Optimization 管理科学-工程：综合

CiteScore

5.90

自引率

7.40%

发文量

审稿时长

3.5 months

期刊介绍： Engineering Optimization is an interdisciplinary engineering journal which serves the large technical community concerned with quantitative computational methods of optimization, and their application to engineering planning, design, manufacture and operational processes. The policy of the journal treats optimization as any formalized numerical process for improvement. Algorithms for numerical optimization are therefore mainstream for the journal, but equally welcome are papers which use the methods of operations research, decision support, statistical decision theory, systems theory, logical inference, knowledge-based systems, artificial intelligence, information theory and processing, and all methods which can be used in the quantitative modelling of the decision-making process. Innovation in optimization is an essential attribute of all papers but engineering applicability is equally vital. Engineering Optimization aims to cover all disciplines within the engineering community though its main focus is in the areas of environmental, civil, mechanical, aerospace and manufacturing engineering. Papers on both research aspects and practical industrial implementations are welcomed.