Evaluation Method of Product Shape Features based on Multidimension Spatial Data Mining

Feilong Liu, Miao Li and Gengxin Sun

Mathematical Problems in Engineering, 2022, vol. 2022, 1-11

Abstract: Analysis of product shape design has attracted more and more attention of researchers because it can make products better meet perceptual needs. Based on the theory of spatial data mining, this study proposes an evaluation method of a product shape design scheme. The method proposed in this study not only obtains the shape design of the overall and local features of the product, which solves the problem of the insufficient utilization of spatial data by the analysis method. During the simulation process, the model obtains the product shape design and appeal from the online evaluation spatial data, which can integrate the product perceptual knowledge in the spatial data, which greatly reduces the manual operation steps and the required time for the degree of data utilization. The experimental results show that after the obtained data are filtered to extract the feature words, the weight of the feature words is calculated by the TF-IDF method, the number of neighbors is increased from 1 to 30, the interval is 5, and the vectorized representation of the spatial data is constructed. The similarity between the calculation sentences of the data mining method is 89.7%, which effectively improves the support function and design efficiency of spatial data mining for product design.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:hin:jnlmpe:1111683

DOI: 10.1155/2022/1111683

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