4.7 Article

BERT and Pareto dominance applied to biological strategy decision for bio-inspired design

期刊

ADVANCED ENGINEERING INFORMATICS
卷 55, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.aei.2023.101904

关键词

Bio-inspired design; Biological strategy; BERT; Pareto dominance; Preference-based

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Bio-inspired design (BID) approaches have provided innovative design proposals, but also led to an explosion of alternatives. Choosing personalized recommendations has become more difficult, and engineer may prefer fewer goals. However, the diversity and feasibility of BID often contradict each other. To address these issues, this study proposes a interdisciplinary approach using BERT and Pareto dominance theory for biological strategy decision (BPBSD) in BID. Experimental results demonstrate the effectiveness of BPBSD in balancing diversity and feasibility in BID, providing practical guidance for BID.
Bio-inspired design (BID) approaches have provided numerous novel proposals for innovative design. Mean-while, it resulted in an explosion of alternatives. Choosing a small amount of the personalized recommendations is becoming more and more difficult, and engineers may prefer fewer goals. Furthermore, engineers may choose designs that have variety and feasibility in BID. However, the diversity and feasibility of BID are often contradictory. Engineers need to apply multi-objective optimization methods to find better BID to ensure implementable. Aiming to overcome the above problems, based on the biological strategies from the most popular BID-AskNature, we proposed an interdisciplinary approach with the bidirectional encoder representation from transformers (BERT) and Pareto dominance for biological strategy decision (BPBSD) in the BID. First, we use BERT to find potential biological strategies similar to the keyword of BID. Then, aiming at the functional diversity and the feasibility of BID, we used the Pareto dominance theory to solve the contradiction. Finally, we verify the effectiveness of the proposed approach with three different application cases. Experiments show that the proposed BPBSD can balance the relationship between diversity and feasibility in BID. It is hoped that this work provides practical guidance for BID.

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