Research on the image of sweeping robot based on the Artificial Neural Network

Chang Song; Yoshito Ogata

doi:10.1051/matecconf/201713900059

Research on the image of sweeping robot based on the Artificial Neural Network

Research output: Contribution to journal › Conference article › peer-review

Abstract

Based on the theory of Artificial Neural Network and Kansei Engineering, the image of sweeping robots are formed using the content analysis method, and propose four kinds of sweeping robot as the experimental samples, which have a strong influence on the market. The image questionnaires are compiled by the semantic differences methods. 200 office workers, half men and half women, are chose as the survey respondents. And use SPSS statistical software for data analysis. Afterwards, the BP Artificial Neural Network model is established by Matlab based on the questionnaire results, and the optimized design scheme with image feature combination for sweeping robot products is generated on the basis of BP Artificial Neural Network model. This study construct the emotional demands on the image level, and carry out experiments and statistical analysis, which lays a solid foundation for the study of product image in theory and approach.

Original language	English
Article number	00059
Journal	MATEC Web of Conferences
Volume	139
DOIs	https://doi.org/10.1051/matecconf/201713900059
Publication status	Published - Dec 5 2017
Event	3rd International Conference on Mechanical, Electronic and Information Technology Engineering, ICMITE 2017 - Chengdu, China Duration: Dec 16 2017 → Dec 17 2017

All Science Journal Classification (ASJC) codes

Chemistry(all)
Materials Science(all)
Engineering(all)

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10.1051/matecconf/201713900059

Cite this

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title = "Research on the image of sweeping robot based on the Artificial Neural Network",

abstract = "Based on the theory of Artificial Neural Network and Kansei Engineering, the image of sweeping robots are formed using the content analysis method, and propose four kinds of sweeping robot as the experimental samples, which have a strong influence on the market. The image questionnaires are compiled by the semantic differences methods. 200 office workers, half men and half women, are chose as the survey respondents. And use SPSS statistical software for data analysis. Afterwards, the BP Artificial Neural Network model is established by Matlab based on the questionnaire results, and the optimized design scheme with image feature combination for sweeping robot products is generated on the basis of BP Artificial Neural Network model. This study construct the emotional demands on the image level, and carry out experiments and statistical analysis, which lays a solid foundation for the study of product image in theory and approach.",

author = "Chang Song and Yoshito Ogata",

note = "Funding Information: Supported by China Scholarship Council (CSC). Publisher Copyright: {\textcopyright} The Authors, published by EDP Sciences, 2017.; 3rd International Conference on Mechanical, Electronic and Information Technology Engineering, ICMITE 2017 ; Conference date: 16-12-2017 Through 17-12-2017",

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doi = "10.1051/matecconf/201713900059",

language = "English",

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TY - JOUR

T1 - Research on the image of sweeping robot based on the Artificial Neural Network

AU - Song, Chang

AU - Ogata, Yoshito

N1 - Funding Information: Supported by China Scholarship Council (CSC). Publisher Copyright: © The Authors, published by EDP Sciences, 2017.

PY - 2017/12/5

Y1 - 2017/12/5

N2 - Based on the theory of Artificial Neural Network and Kansei Engineering, the image of sweeping robots are formed using the content analysis method, and propose four kinds of sweeping robot as the experimental samples, which have a strong influence on the market. The image questionnaires are compiled by the semantic differences methods. 200 office workers, half men and half women, are chose as the survey respondents. And use SPSS statistical software for data analysis. Afterwards, the BP Artificial Neural Network model is established by Matlab based on the questionnaire results, and the optimized design scheme with image feature combination for sweeping robot products is generated on the basis of BP Artificial Neural Network model. This study construct the emotional demands on the image level, and carry out experiments and statistical analysis, which lays a solid foundation for the study of product image in theory and approach.

AB - Based on the theory of Artificial Neural Network and Kansei Engineering, the image of sweeping robots are formed using the content analysis method, and propose four kinds of sweeping robot as the experimental samples, which have a strong influence on the market. The image questionnaires are compiled by the semantic differences methods. 200 office workers, half men and half women, are chose as the survey respondents. And use SPSS statistical software for data analysis. Afterwards, the BP Artificial Neural Network model is established by Matlab based on the questionnaire results, and the optimized design scheme with image feature combination for sweeping robot products is generated on the basis of BP Artificial Neural Network model. This study construct the emotional demands on the image level, and carry out experiments and statistical analysis, which lays a solid foundation for the study of product image in theory and approach.

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DO - 10.1051/matecconf/201713900059

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SN - 2261-236X

VL - 139

JO - MATEC Web of Conferences

JF - MATEC Web of Conferences

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T2 - 3rd International Conference on Mechanical, Electronic and Information Technology Engineering, ICMITE 2017

Y2 - 16 December 2017 through 17 December 2017

ER -

Research on the image of sweeping robot based on the Artificial Neural Network

Abstract

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