An application of fuzzy linguistic summarization and fuzzy association rule mining to Kansei Engineering: a case study on cradle design

Akgül, Esra; Delice, Yılmaz; Aydoğan, Emel Kızılkaya; Boran, Fatih Emre

doi:10.1007/s12652-021-03292-9

Cited by 13 publications

(5 citation statements)

References 73 publications

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“…As a method and theory of product development, Kansei Engineering takes the impression, feeling or demand of consumers on products as the design orientation, and transforms the description of such mental images into design elements [15][16]. Its purpose is to break the previous design concept of paying more attention to product function and form, and strive to improve the attention of users or consumers' intentions and needs in the process of design and development of products.…”

Section: Kansei Engineeringmentioning

confidence: 99%

Machine Vision Prediction Model for Product Color Design by Kansei Engineering

Han

2024

Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development,

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Color is a visual element of people, it can bring people different levels, different feelings, and can make people have associations and emotional resonance. Under the background of Kansei engineering, product color design is an important research field. This paper aims to discuss the predictive model of Kansei engineering in product color design, in order to improve the quality of products and meet the needs of consumers. Through empirical research and user survey, this paper verifies the accuracy and effectiveness of product color perceptual image generated by machine vision prediction model for the elderly products. The survey and experimental results show that support vector machines perform best, with an accuracy of 91% and a recall rate 4% higher than BP neural networks.

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Section: Kansei Engineeringmentioning

confidence: 99%

Machine Vision Prediction Model for Product Color Design by Kansei Engineering

Han

2024

Proceedings of the First International Conference on Science, Engineering and Technology Practices for Sustainable Development,

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“…It was verifed that the GA-based ANN has better prediction accuracy in modeling compared to the traditional ANN [22]. Akgül et al's application of fuzzy association rules and GA to transform the emotional needs of a cradle chair into design elements demonstrates that GA can assist in exploring superior design solutions [23]. Furthermore, applying BPNN, GRNN, GA-BPNN, and QTTI simultaneously to the construction of imagery models for product sound, the results of the research indicate that GA-BPNN is less cost-efective and time-consuming compared to traditional algorithms in the feld of product sound [24].…”

Section: Genetic Algorithm-based Bpnnmentioning

confidence: 99%

Multisensory Design of Electric Shavers Based on Kansei Engineering and Artificial Neural Networks

Lin

Woo

Luo

et al. 2023

Mathematical Problems in Engineering

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The market scale of electric shavers in China has reached ¥ 26.3 billion in 2021. Consumers currently place an increasing emphasis on the Kansei image conveyed by products rather than just concerning with functional satisfaction. To meet consumers’ expectations, the emotional message conveyed by product design is essential under multisensory channels. This research first collected 230 electric shavers samples and 135 pairs of consumers’ Kansei words, then reduced them into 34 representative samples using multidimensional scale and clustering analysis, with 4 groups of representative Kansei words selected via the expert group. Moreover, consumers’ Kansei images were evaluated via questionnaire using the semantic differential scales, with 416 valid samples acquired in total. Meanwhile, design elements of the samples (including item and category) were classified by ways of morphological analysis and audio software. At last, the prediction models of the electric shavers were established between the overall design elements and user’s Kansei evaluation under the multisensory channel of visual model and auditory audio taking advantage of Quantification Theory Type I , back propagation neural network, and genetic algorithm-based BPNN. The proposed models can provide defined design indexes and references in multisensory design, facilitating designers to design in a logical and scientific manner rather than designing as per experience.

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“…Qualifiers, which enrich the summaries by adding detail, are modeled on the basis of fuzzy sets, like summaries and quantifiers, and the membership degrees of the data are extracted according to the labels. TD of the summaries in the Type-2 quantifier protoform is calculated as in Eq.8 67,68 ;…”

Section: Type-2 Quantified Sentencementioning

confidence: 99%

Neurocognitive Responses to Spatial Design Behaviors and Tools Among Interior Architecture Students: A Pilot Study

Şekerci,

Kahraman,

Kaya

et al. 2023

Preprint

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The impact of emotions on human behavior is substantial, and the ability to recognize people's feelings has a wide range of practical applications including education. Here, the methods and tools of education are being calibrated according to the data gained over electroencephalogram (EEG) signals. The issue of which design tools would be ideal in the future of interior architecture education, is an uncertain field. It is important to measure the students’ emotional states while using manual and digital design tools to determine the different impacts. Brain-computer interfaces have made it possible to monitor emotional states in a way that is both convenient and economical. In the research of emotion recognition, EEG signals have been employed, and the resulting literature explains basic emotions as well as complicated scenarios that are created from the combination of numerous basic emotions. Linguistic summarization is a technique that can assist in extracting knowledge from huge volumes of data by identifying pre-defined structures and expressing them in a concise manner. The purpose of this research is to investigate the attachment and emotional states of interior architecture students while they are designing in 2D or 3D with manual or digital tools, as well as to investigate differences in the use of design tools and behaviors that are based on teaching methodologies. The study produced summaries of the data using a fuzzy sets-based linguistic summarization technique, and it explained the findings in daily natural language that is easy to understand without expert.

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An application of fuzzy linguistic summarization and fuzzy association rule mining to Kansei Engineering: a case study on cradle design

Cited by 13 publications

References 73 publications

Machine Vision Prediction Model for Product Color Design by Kansei Engineering

Machine Vision Prediction Model for Product Color Design by Kansei Engineering

Multisensory Design of Electric Shavers Based on Kansei Engineering and Artificial Neural Networks

Neurocognitive Responses to Spatial Design Behaviors and Tools Among Interior Architecture Students: A Pilot Study

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