Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers

Biological inspiration evaluation has been widely acknowledged as one of the most important phases in biologically inspired design (BID) as it substantially determines the direction of the following-up design activities. However, it is inherently an interdisciplinary assessment, which includes both...

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Main Authors: Zhu, Guoniu, Ma, Jin, Hu, Jie
Other Authors: School of Mechanical and Aerospace Engineering
Format: Article
Language:English
Published: 2022
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Online Access:https://hdl.handle.net/10356/160596
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1605962022-07-27T06:55:16Z Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers Zhu, Guoniu Ma, Jin Hu, Jie School of Mechanical and Aerospace Engineering Engineering::Mechanical engineering Biological Inspiration Evaluation Biologically Inspired Design Biological inspiration evaluation has been widely acknowledged as one of the most important phases in biologically inspired design (BID) as it substantially determines the direction of the following-up design activities. However, it is inherently an interdisciplinary assessment, which includes both the engineering domain and the biological systems. Due to the lack of knowledge at the early stage of product design, the risk assessments mainly depend on experts' subjective judgments, which values are vague, imprecise, and even inconsistent. How to objectively evaluate the biological inspiration under such uncertain and interdisciplinary scenarios remains an open issue. To bridge such gaps, this study proposes a fuzzy rough number extended multi-criteria group decision-making (MCGDM) to evaluate the biological inspiration for BID. A fuzzy rough number is introduced to represent the individual decision maker's risk assessment and aggregate respective evaluation values within the decision-making group. A fuzzy rough number extended decision-making trial and evaluation laboratory is presented to determine the criteria weights and a fuzzy rough number extended multi-attribute ideal real comparative analysis is proposed to rank the candidate biological inspirations. Experimental results and comparative analysis validate the superiority of the proposed MCGDM in handling the subjectivity and uncertainty in biological inspiration evaluation. This study was partly supported by the Shanghai Pujiang Program (Grant/Award No. 20PJ1406600). 2022-07-27T06:55:16Z 2022-07-27T06:55:16Z 2021 Journal Article Zhu, G., Ma, J. & Hu, J. (2021). Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers. International Journal of Intelligent Systems, 36(10), 6032-6065. https://dx.doi.org/10.1002/int.22541 0884-8173 https://hdl.handle.net/10356/160596 10.1002/int.22541 2-s2.0-85108285946 10 36 6032 6065 en International Journal of Intelligent Systems © 2021 Wiley Periodicals LLC. All rights reserved.
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering
Biological Inspiration Evaluation
Biologically Inspired Design
spellingShingle Engineering::Mechanical engineering
Biological Inspiration Evaluation
Biologically Inspired Design
Zhu, Guoniu
Ma, Jin
Hu, Jie
Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers
description Biological inspiration evaluation has been widely acknowledged as one of the most important phases in biologically inspired design (BID) as it substantially determines the direction of the following-up design activities. However, it is inherently an interdisciplinary assessment, which includes both the engineering domain and the biological systems. Due to the lack of knowledge at the early stage of product design, the risk assessments mainly depend on experts' subjective judgments, which values are vague, imprecise, and even inconsistent. How to objectively evaluate the biological inspiration under such uncertain and interdisciplinary scenarios remains an open issue. To bridge such gaps, this study proposes a fuzzy rough number extended multi-criteria group decision-making (MCGDM) to evaluate the biological inspiration for BID. A fuzzy rough number is introduced to represent the individual decision maker's risk assessment and aggregate respective evaluation values within the decision-making group. A fuzzy rough number extended decision-making trial and evaluation laboratory is presented to determine the criteria weights and a fuzzy rough number extended multi-attribute ideal real comparative analysis is proposed to rank the candidate biological inspirations. Experimental results and comparative analysis validate the superiority of the proposed MCGDM in handling the subjectivity and uncertainty in biological inspiration evaluation.
author2 School of Mechanical and Aerospace Engineering
author_facet School of Mechanical and Aerospace Engineering
Zhu, Guoniu
Ma, Jin
Hu, Jie
format Article
author Zhu, Guoniu
Ma, Jin
Hu, Jie
author_sort Zhu, Guoniu
title Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers
title_short Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers
title_full Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers
title_fullStr Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers
title_full_unstemmed Evaluating biological inspiration for biologically inspired design: an integrated DEMATEL-MAIRCA based on fuzzy rough numbers
title_sort evaluating biological inspiration for biologically inspired design: an integrated dematel-mairca based on fuzzy rough numbers
publishDate 2022
url https://hdl.handle.net/10356/160596
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