ArticleBiomimetics (Basel, Switzerland)2024
A Parameter Reduction-Based Decision-Making Method with Interval-Valued Neutrosophic Soft Sets for the Selection of Bionic Thin-Wall Structures.
Article in Biomimetics (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Mechanical Analysis and Multi-Objective Optimization of Origami-Inspired Tree-Shaped Thin-Walled Structures Under Axial Impacts.Biomimetics (Basel, Switzerland) · 2025Article
- Intelligent Automobile Bionic Cockpit Selection Considering Personalization Requirements: Multiple-Criterion Model and Decision-Making Method.Biomimetics (Basel, Switzerland) · 2025Article
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6 authors.
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Abstract
Bio-inspired thin-wall structures with excellent mechanical properties, high-energy absorption capabilities, and a desirable lightweight level have been extensively applied to the passive safety protection of transportation and aerospace. Collaboration matching and the selection of optional structures with different bionic principles considering the multiple attribute evaluation index and engineering preference information have become an urgent problem. This paper proposes a parameter reduction-based indifference threshold-based attribute ratio analysis method under an interval-valued neutrosophic soft set (IVNS-SOFT) to obtain the weight vector of an evaluation indicator system for the selection of bionic thin-wall structures, which can avoid the problem of an inadequate subjective evaluation and reduce redundant parameters. An IVNS-SOFT-based multi-attributive border approximation area comparison (MABAC) method is proposed to obtain an optimal alternative, which can quantify uncertainty explicitly and handle the uncertain and inconsistent information prevalent in the expert system. Subsequently, an application of five bio-inspired thin-wall structures is applied to demonstrate that this proposed method is valid and practical. Comparative analysis, sensitivity analysis, and discussion are conducted in this research. The results show that this study provides an effective tool for the selection of bionic thin-wall structures.
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