A linguistic representation based approach to modelling Kansei data and its application to consumer-oriented evaluation of traditional products

Chanyachatchawan, Sapa; Yan, Haowen; Sriboonchitta, Songsak; Huynh, Van–Nam

doi:10.1016/j.knosys.2017.09.037

Cited by 19 publications

(11 citation statements)

References 39 publications

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“…Then, they analyzed the user perception and understanding, thereby improving the research efficiency of the product's emotional design. Chanyachatchawan et al (2017) proposed a linguistic variable based on the perceptual data and applied a fuzzy probability to model the proposed variable. They obtained the user's emotional attribute judgment on the product.…”

Section: Related Workmentioning

confidence: 99%

Evaluating aircraft cockpit emotion through a neural network approach

Chen

Chu

et al. 2020

AIEDAM

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Studies show that there are shortcomings in applying conventional methods for the emotional evaluation of the aircraft cockpit. In order to resolve this problem, a more efficient cockpit emotion evaluation system is established in the present study to simply and quickly obtain the cockpit emotion evaluation value. To this end, the neural network is applied to construct an emotional model to evaluate the emotional prediction of the interior design of the aircraft cockpit. Moreover, several technologies and the Kansei engineering method are applied to acquire the cockpit interior emotional evaluation data for typical aircraft models. In this regard, the radical basis function neural network (RBFNN), Elman neural network (ENN), and the general regression neural network (GRNN) are applied to construct the sentimental prediction evaluation model. Then, the three models are comprehensively compared through factors such as the model evaluation criteria, network structure, and network parameters. Obtained experimental results indicate that the GRNN not only has the highest classification accuracy but also has the highest stability in comparison to the other two neural networks, so that it is a more appropriate method for the emotional evaluation of the aircraft cockpit. Results of the present study provide decision supports for the emotional evaluation of the cockpit interior space.

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Section: Related Workmentioning

confidence: 99%

Evaluating aircraft cockpit emotion through a neural network approach

Chen

Chu

et al. 2020

AIEDAM

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“…Subintervals of the domain, derived from the α-cut of semantics of terms, are utilized to compute the value functions. The linguistic aspiration levels in [60] and [79] are also single terms. Others in Table 7 did not consider the aspirations of experts.…”

Section: ) Regarding Aspiration-based Approachesmentioning

confidence: 99%

An Aspiration-Based Approach for Qualitative Decision-Making With Complex Linguistic Expressions

Wang

Zhang

et al. 2019

IEEE Access

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Decisions are usually made based on not only the performances of alternatives but also are implied by how the performances satisfy the decision makers' aspiration levels. This paper presents a linguistic aspiration-based solution to qualitative decision-making (QDM) where the aspiration levels and performances can be expressed by complex linguistic expressions (CLEs) such as hesitant fuzzy linguistic term sets and linguistic terms with weakened hedges. The proposed approach can deal with complex problems, which involve multi-criteria, multi-groups of experts, and multi-granular linguistic information. Based on the conventional aspiration-based approaches, the value function is defined by the probability of a CLE achieving its linguistic aspiration level. The performance of the proposed QDM approach is then demonstrated by solving the problem regarding the provider evaluation and selection. The proposed approach extends the range of available natural linguistic expressions that can be considered and used by experts and emphasizes the role of linguistic aspiration levels in QDM.

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“…2 below describes forward Kansei engineering system [18], [19]. Several steps on data processing in KE type 2 are performed as follow [19]: 1) Determining the objective of the study. 2) Collecting consumers' need and feeling to obtain the Kansei words.…”

Section: ) Develops the Parameter Of Doll Designmentioning

confidence: 99%

Educative Doll Design as Media for Learning Indonesian Traditional Folk Song Using Affective Design Approach

Soewardi¹,

Maulidyawati²

2018

IJIET

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Over the past decade, modernity has become a mainstream factor of entertainment. Unfortunately, it makes traditional things be abandoned slowly, especially in Indonesia. However, the lack of traditional products that can attract users' attention is influenced by the designs from the manufacturers. Thus, the objective of this research is to develop an innovative education doll as media of learning Indonesian folk songs. Kansei Engineering (KE) method and Fuzzy Linguistics principle were used to design. More than 100 respondents were involved in this study to identify the Kansei words. This is because these methods support emotional response of the users in affective design approach. Potential attributes in developing a new single concept design were analysed using Orthogonal array and conjoint analysis. Then, the data were analysed using statistical analysis. This study resulted in an innovative education doll that is proven to be valid in meeting the consumers' requirement.Index Terms-Educative doll design, Indonesian traditional folk song, affective design, kansei engineering, fuzzy linguistic.

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A linguistic representation based approach to modelling Kansei data and its application to consumer-oriented evaluation of traditional products

Cited by 19 publications

References 39 publications

Evaluating aircraft cockpit emotion through a neural network approach

Evaluating aircraft cockpit emotion through a neural network approach

An Aspiration-Based Approach for Qualitative Decision-Making With Complex Linguistic Expressions

Educative Doll Design as Media for Learning Indonesian Traditional Folk Song Using Affective Design Approach

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