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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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. |
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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 |
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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. |
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School of Mechanical and Aerospace Engineering |
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School of Mechanical and Aerospace Engineering Zhu, Guoniu Ma, Jin Hu, Jie |
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Article |
author |
Zhu, Guoniu Ma, Jin Hu, Jie |
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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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1739837471824281600 |