Zöller S, Schröppel T, Wartzack S (2017)
Publication Language: German
Publication Type: Conference contribution, Conference Contribution
Publication year: 2017
Publisher: TuTech Verlag
City/Town: Hamburg
Pages Range: 287-298
Conference Proceedings Title: Design for X. Beiträge zum 28. DfX-Symposium
Event location: Bamberg
ISBN: 978-3-946094-20-3
URI: https://www.archiv.mfk.tf.fau.de?file=pubmfk_59d73ca418f63
Affective Engineering (AE) is an engineering genre that deals with users’ subjective value creation in technical product design. Therein, quantitative instruments to map subjective quality criteria are dominant. ACADE is such an instrument that focuses on a long-term alignment of product design impres-sions to the subjective needs of users. Due to its quantitative backbone, sev-eral mathematical analysis methods seem convenient, whereas their specific benefits and drawbacks are not yet clear in the AE context. Therefore, anal-yses of nonlinear regression, artificial neural networks, fuzzy logic systems and hybrids are examined under the aspect of ACADE applicability. Different quality indicators unveil characteristics which the designer may use to mine their potential for future AE analyses.
APA:
Zöller, S., Schröppel, T., & Wartzack, S. (2017). Ein Vergleich von Datenanalysemethoden für eine Affective Engineering Methode. In Krause, D.; Paetzold, K.; Wartzack, S. (Hrg.), Design for X. Beiträge zum 28. DfX-Symposium (S. 287-298). Bamberg: Hamburg: TuTech Verlag.
MLA:
Zöller, Susan, Tina Schröppel, and Sandro Wartzack. "Ein Vergleich von Datenanalysemethoden für eine Affective Engineering Methode." Tagungsband 28. DfX-Symposium, Bamberg Hrg. Krause, D.; Paetzold, K.; Wartzack, S., Hamburg: TuTech Verlag, 2017. 287-298.
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