Evidence map›Paper›PMID 41990040›Full record

ArticlePloS one2026

An adaptive extended radial basis function based interval analysis method for structural engineering solutions.

Xu Jitang, He Jinli, Chen Qiang

Abstract read
In one paragraph

Article in PloS one, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

3 authors.

Xu JitangDepartment of Transportation and Construction, Tianjin Bohai Vocational Technical Collage, Tianjin, China.ORCID https://orcid.org/0009-0001-4741-381X
He JinliTianjin Bohai Vocational Technical College, Tianjin, China.
Chen QiangBeijing Zhongyu Shenzhou Data Technology Co., LTD, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In engineering structures, uncertain interval analysis is a study hotspot. However, how to obtain the accurate and efficient upper and lower solution bounds of uncertainty in the uncertain interval analysis is one of the key problems at present. To address this issue, the paper proposes a new adaptive extended radial basis function based interval analysis method to obtain accurate and efficient structural bound solutions. Instead of the pre-selecting the width of the basis functions, an Extended Radial Basis Function (E-RBF) and the adjusted widths are combined to confirm each width of the Gaussian basis function. In order to obtain the widths of the Gaussian basis function, the adaptive scaling technique is introduced in the E-RBF model. Then six numerical functions are selected to evaluate the accuracy of the E-RBF method with adjusted widths. On the basis of ensuring the accuracy of the widths of the Gaussian basis function, the adaptive E-RBF based interval analysis method is constructed by using the E-RBF with adjusted widths, catching the critical points and establishing the adaptive procedure for solving the extreme certain interval bounds of complex structural engineering problems. Next, three structural numerical examples and one composite shell are produced to verify the validity and effectiveness of this adaptive E-RBF based interval analysis method.

Indexed as

EngineeringModels, TheoreticalAlgorithmsRadial Basis Function NetworksUncertainty

Identifiers

PMID41990040
PMCPMC13086358

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.