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

机译:基于人工神经网络的清扫机器人图像研究

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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.
机译:基于人工神经网络和KANSEI工程理论,使用内容分析方法形成了扫描机器人的形象,并提出了四种综合机器人作为实验样本,对市场产生了强烈影响。图像问卷由语义差异方法编译。 200个办公室工作人员,半人和半妇女被选择为调查受访者。并使用SPSS统计软件进行数据分析。之后,基于调查问卷结果,MATLAB建立了BP人工神经网络模型,并在BP人工神经网络模型的基础上产生了具有用于扫描机器人产品的图像特征组合的优化设计方案。本研究构建了对图像水平的情绪需求,并进行实验和统计分析,为理论和方法研究了产品形象的稳固基础。

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