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Similar case retrieval method based on multidimensional correlation function

A correlation function and multi-dimensional technology, which is applied in the field of similar instance retrieval based on multi-dimensional correlation functions, can solve problems such as the inability to reflect the difference between multi-dimensional attribute input and single-dimensional attribute input.

Active Publication Date: 2015-03-25
ZHEJIANG UNIV OF TECH
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Problems solved by technology

Moreover, complex products have multiple attributes of different dimensions. The traditional method is to calculate the similarity of a single attribute first, and then integrate and solve the similarity of the global attribute, but it cannot reflect the difference between multi-dimensional attribute input and single-dimensional attribute input.

Method used

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  • Similar case retrieval method based on multidimensional correlation function
  • Similar case retrieval method based on multidimensional correlation function
  • Similar case retrieval method based on multidimensional correlation function

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[0047] refer to figure 1 and figure 2 , a similar instance retrieval method based on a multidimensional correlation function, the method includes the following steps:

[0048] (1) Side distance for low-carbon design

[0049] The side distance mainly considers the bias of the position of the optimal value of the product design parameters and accurately gives the calculation formula of the distance between the design parameter point and the design target interval. Therefore, when considering the optimal value of the design parameters, the calculation efficiency of the distance between the design parameter point and the optimal value is obviously not static, but a curve with a variable slope.

[0050] Assume that the section field X of a certain attribute of the product=, x 0 is the optimal point value of this attribute, then the left distance from x to interval X can be expressed as:

[0051] ρ Il ( x ...

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Abstract

A similar case retrieval method based on a multidimensional correlation function includes the steps of firstly, improving the lateral spacing through a variable slope method, and establishing a multidimensional lateral spacing model based on the improved lateral spacing; secondly, establishing the multidimensional correlation function with a good dimensionality reduction effect under the relatively-complex multidimensional lateral spacing calculation; thirdly, putting forward a three-stage low-carbon product retrieval method based on the multidimensional correlation function. By means of the similar case retrieval method based on the multidimensional correlation function, the data dimensionality calculation can be reduced, the retrieval efficiency can be improved, and the more accurate and reliable result can be obtained.

Description

technical field [0001] The invention relates to the technical field of low-carbon design, in particular to a method for retrieving similar instances based on multidimensional correlation functions. Background technique [0002] As one of the energy-saving ecological design technologies, low-carbon design is a modern design method that comprehensively considers carbon emissions and high efficiency and energy saving under the premise of ensuring the functions, quality and life of the product. Focused research on lightweight design and module design. The analysis and modeling of product carbon footprint is the basis of low-carbon design method research. At present, most of the researches focus on the low-carbon demand of products only on the quantitative calculation of product carbon footprint. influences. [0003] In the process of development, low-carbon products are constantly being updated to meet the needs of the market, and the types and quantities of product examples a...

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Application Information

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IPC IPC(8): G06F17/15
Inventor 赵燕伟洪欢欢任设东陈尉刚
Owner ZHEJIANG UNIV OF TECH
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