Grey relational analysis based artificial neural networks for product design: A comparative study

Yang Cheng Lin, Chung Hsing Yeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

Artificial neural networks (ANNs) have been applied successfully in a wide range of fields due to its effective learning ability. In this paper, we propose a grey relational analysis (GRA) based ANN model that can be used to build a design decision support database for facilitating the product design process and matching specific consumers' preferences. The result of an empirical application and a comparative study on fragrance bottle form design shows that the ANN models outperform the grey prediction models, indicating that the ANN technique is promising to help product designers design a new product that best meets consumers' needs.

Original languageEnglish
Title of host publicationICINCO 2015 - 12th International Conference on Informatics in Control, Automation and Robotics, Proceedings
EditorsJoaquim Filipe, Joaquim Filipe, Jurek Sasiadek, Oleg Gusikhin, Kurosh Madani
PublisherSciTePress
Pages653-658
Number of pages6
ISBN (Electronic)9789897581229
Publication statusPublished - 2015 Jan 1
Event12th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2015 - Colmar, Alsace, France
Duration: 2015 Jul 212015 Jul 23

Publication series

NameICINCO 2015 - 12th International Conference on Informatics in Control, Automation and Robotics, Proceedings
Volume1

Other

Other12th International Conference on Informatics in Control, Automation and Robotics, ICINCO 2015
CountryFrance
CityColmar, Alsace
Period15-07-2115-07-23

All Science Journal Classification (ASJC) codes

  • Information Systems
  • Control and Systems Engineering
  • Computer Vision and Pattern Recognition

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