Research on innovative methods based on clustering and case-based reasoning

Kun Shang

doi:10.1117/12.2611658

11 November 2021 Research on innovative methods based on clustering and case-based reasoning

Kun Shang

Proceedings Volume 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence; 1207612 (2021) https://doi.org/10.1117/12.2611658
Event: Fourth International Conference on Image, Video Processing, and Artificial Intelligence (IVPAI 2021), 2021, Shanghai, China

Abstract

Innovation is one of the decisive factors for the prosperity of an enterprise. The Theory of Inventive Problem Solving (TRIZ) is an effective method to promote system innovative design. However, TRIZ solution is a highly abstract conceptual solution, and its transformation to a specific solution requires a large amount of rich knowledge from different engineering fields. Designers themselves cannot master all the supporting knowledge required for problem solving, which increases the difficulty of TRIZ in practical application. In order to overcome these difficulties, this paper presents a method synthesizing TRIZ, CBR and GHSOM, in which TRIZ can systematically generate innovative solutions, CBR makes designers take full advantage of past experience and knowledge to transform abstract TRIZ solutions into solutions to specific design problems, and GHSOM as a clustering tool expands the scope of knowledge utilization and promote the diversification of design solutions. Finally, an example is given to illustrate the method.

Citation Download Citation

Kun Shang "Research on innovative methods based on clustering and case-based reasoning", Proc. SPIE 12076, 2021 International Conference on Image, Video Processing, and Artificial Intelligence, 1207612 (11 November 2021); https://doi.org/10.1117/12.2611658

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