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.
|Journal||MATEC Web of Conferences|
|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
- Materials Science(all)