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A Green-IKE Inference System Based on Grey Neural Network Model for Humanized Sustainable Feeling Assessment about Products
Joint Authors
Wang, Kun-Chieh
Wu, Long
Gao, Hao
Yang, Chi-Hsin
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-01-28
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Abstract EN
Due to extraordinary concerns about the issue of environmental protection from time to time, so far, sustainable development draws much attention.
In developing sustainable products, the studies on methodologies of how to precisely grasp the sustainable feeling about products and translate it into desired constructed elements are scarce.
This study aims to propose a novel sustainable feeling assessment system about products, called green-initiative Kansei engineering (GIKE).
The Kansei engineering scheme is a distinguished customer-oriented technology for dealing with peoples’ affection about concerning matters.
In this study, we extend Kansei engineering to initiatively include the designated sustainable image other than statistically obtained high-ranking images.
Then, through survey and analysis of concerning matters, we precisely build a GIKE inference system via the grey-model-based backpropagation neural network scheme, in which it provides a precise relationship between affective (including sustainable) images of products and their constructive elements.
A computer mouse is selected as the target in experiments to verify the proposed methodology, and the result is satisfying.
Through our study, we may know the way to acquire a human’s sustainable feeling about concerning matters.
And, most importantly, the proposed GIKE methodology firstly and innovatively expands the application filed of Kansei engineering to the field of sustainability evaluation and translation for concerning matters.
American Psychological Association (APA)
Wu, Long& Gao, Hao& Wang, Kun-Chieh& Yang, Chi-Hsin. 2020. A Green-IKE Inference System Based on Grey Neural Network Model for Humanized Sustainable Feeling Assessment about Products. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1196758
Modern Language Association (MLA)
Wu, Long…[et al.]. A Green-IKE Inference System Based on Grey Neural Network Model for Humanized Sustainable Feeling Assessment about Products. Mathematical Problems in Engineering No. 2020 (2020), pp.1-9.
https://search.emarefa.net/detail/BIM-1196758
American Medical Association (AMA)
Wu, Long& Gao, Hao& Wang, Kun-Chieh& Yang, Chi-Hsin. A Green-IKE Inference System Based on Grey Neural Network Model for Humanized Sustainable Feeling Assessment about Products. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-9.
https://search.emarefa.net/detail/BIM-1196758
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1196758