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IMPROVING SCENARIO-TECHNIQUE BY A SEMI-AUTOMATIZED CONSISTENCY ASSESSMENT BASED ON PATTERN RECOGNITION BY ARTIFICIAL NEURAL NETWORKS

Part of: Design Support Tools

Published online by Cambridge University Press:  11 June 2020

I. Gräßler ,
P. Scholle  and
H. Thiele
I. Gräßler
Affiliation:
Paderborn University, Germany
P. Scholle*
Affiliation:
Paderborn University, Germany
H. Thiele
Affiliation:
Paderborn University, Germany
*
*philipp.scholle@hni.uni-paderborn.de

Abstract

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To enhance the success of innovations, various methods for foresight have been developed. Automatization yields the potential of shifting effort away from the process to the actual in-depth analysis of resulting scenarios in scenario-technique. Within this paper, an approach based on a user-specific classification of input factors (consistency values) is presented. Generic consistency patterns used for a semi-automatized consistency assessment based on artificial neural networks are identified using a case study approach. Hereby, the effort for scenario-technique can be reduced significantly.

Keywords

design automationdesign support systemartificial intelligence (AI)scenario technique

Information

Type
Article
Information
Proceedings of the Design Society: DESIGN Conference , Volume 1 , May 2020 , pp. 147 - 156
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2020. Published by Cambridge University Press

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