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A methodology of generating customer satisfaction models for new product development using a neuro-fuzzy approach

机译:使用神经模糊方法为新产品开发生成客户满意度模型的方法

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摘要

When developing new products it is important for design teams to understand customer perceptions of consumer products because the success of such products is heavily dependent upon the associated customer satisfaction level. The chance of a new product's success in a marketplace is higher if users are satisfied with it. In this study, a new methodology of generating customer satisfaction models using a neuro-fuzzy approach is proposed. In contrast to previous research, non-linear and explicit customer satisfaction models can be developed with the use of the proposed methodology. An example of notebook computer design is used to illustrate the methodology. The proposed methodology was measured against the benchmark of statistical regression to determine its effectiveness. Experimental results suggested that the proposed approach outperformed the statistical regression method in terms of mean absolute errors and variance of errors.
机译:在开发新产品时,设计团队必须了解客户对消费产品的看法,因为此类产品的成功在很大程度上取决于相关的客户满意度。如果用户对此感到满意,那么新产品在市场上成功的机会就更高。在这项研究中,提出了一种使用神经模糊方法生成客户满意度模型的新方法。与以前的研究相比,可以使用所提出的方法开发非线性和显式的客户满意度模型。笔记本计算机设计的一个示例用于说明该方法。根据统计回归基准对建议的方法进行了测量,以确定其有效性。实验结果表明,该方法在平均绝对误差和误差方差方面均优于统计回归方法。

著录项

  • 来源
    《Expert systems with applications》 |2009年第8期|11262-11270|共9页
  • 作者

    C.K. Kwong; T.C. Wong; K.Y. Chan;

  • 作者单位

    Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University. Hung Horn, Kowloon, Hong Kong;

    Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University. Hung Horn, Kowloon, Hong Kong;

    Digital Ecosystems and Business Intelligence Institute, Curtin University of Technology, Perth, Australia;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    customer satisfaction models; neuro-fuzzy; new product development;

    机译:客户满意度模型;神经模糊新产品开发;

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