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

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 no...
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Autor*in:	Feilong Liu [verfasserIn] Miao Li [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Übergeordnetes Werk:	In: Mathematical Problems in Engineering - Hindawi Limited, 2002, (2022)
Übergeordnetes Werk:	year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1155/2022/1111683

Katalog-ID:	DOAJ021197903

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callnumber-first	T - Technology
author	Feilong Liu
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topic_title	TA1-2040 QA1-939 Evaluation Method of Product Shape Features based on Multidimension Spatial Data Mining
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title	Evaluation Method of Product Shape Features based on Multidimension Spatial Data Mining
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title_full	Evaluation Method of Product Shape Features based on Multidimension Spatial Data Mining
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title_sort	evaluation method of product shape features based on multidimension spatial data mining
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title_auth	Evaluation Method of Product Shape Features based on Multidimension Spatial Data Mining
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.
abstractGer	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.
abstract_unstemmed	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.
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title_short	Evaluation Method of Product Shape Features based on Multidimension Spatial Data Mining
url	https://doi.org/10.1155/2022/1111683 https://doaj.org/article/a607c92e3bff422b99dede42740fb07f http://dx.doi.org/10.1155/2022/1111683 https://doaj.org/toc/1563-5147
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