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Grey clustering analysis method

A technology of gray clustering and analysis method, applied in the field of system science, can solve the problems such as limiting the application of gray clustering analysis theory and large amount of calculation, and achieve the effect of objective evaluation results, accurate evaluation and wide application.

Inactive Publication Date: 2009-10-28
DONGHUA UNIV +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, due to the large amount of calculation, many complex mathematical problems are involved, and high mathematical knowledge requirements are required for personnel, this greatly limits the application of gray clustering analysis theory in actual production.

Method used

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  • Grey clustering analysis method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0043] The invention is applicable to the material field, and the performance of various materials is comprehensively evaluated by using the invention.

[0044] (1) Select bamboo fiber, cotton fiber, viscose fiber, polyester, Model, Tencel, and male silk as the clustering objects, and select the index of breaking strength and elastic recovery rate to indicate the mechanical properties of the fiber, and the moisture regain and mass specific resistance to indicate the comfort of the fiber The performance index is used as a clustering index, and the number of clustering whitening is shown in Table 1.

[0045] Table 1 Performance values ​​of various fibers

[0046]

[0047] (2) Bring the clustering whitening number into the general program written

[0048] (3) Gray evaluation based on the results

[0049] ① Results of valuation method

[0050] ans=

[0051] 0.5081 0.6250 0.5107

[0052] 0.2550 0.6250 0.7566

[0053] 0.6295 0.4375 0.3810

[0054] 0.4900 0.2500 0.4869

[...

Embodiment 2

[0074] The present invention is applicable to the field of textiles. The present invention is used to comprehensively evaluate the moisture-conducting and quick-drying performance of fabrics designed from a new type of polyester yarn. Comprehensive indicators.

[0075] (1) Select the fabric whose warp is Coolmax yarn, weft yarn is Coolmax yarn, warp yarn is Coolmax yarn, weft yarn is bamboo / cotton 55 / 45 yarn, and pure cotton, pure bamboo and polyester / cotton fabrics of the same specification are clustered Object; air flow, moisture permeability, wicking height, and moisture conduction comprehensive indicators are selected as clustering indicators.

[0076] The woven pure Coolmax fabric and the fabric interwoven with Coolmax and bamboo / cotton were respectively numbered 1 and 2, and the other three were numbered 3, 4, and 5 respectively. The clustering whitening numbers are shown in Table 2.

[0077] Table 2 fabric performance test table

[0078]

[0079] (2) Bring the clus...

Embodiment 3

[0097] The invention is applicable to the field of management, and the invention is used to comprehensively evaluate the ventilation and dust prevention work of mining enterprises.

[0098] (1) Selecting Gongchangling Mine, Longyan Mine, Jingtieshan Mine, Meishan Mine, Chengchao Mine, Daye Mine, and Jinshandian Mine as clustering objects, functional department management index, ventilation and dust prevention equipment management index, operation The environmental management index and employee health management index are clustering indicators, and the number of clustering whitening is shown in Table 3.

[0099] Table 3 Management index of each mine

[0100]

[0101] (2) Bring the clustering whitening number into the general program written

[0102] (3) Gray evaluation based on the results

[0103] ① Results of valuation method

[0104] ans=

[0105] 0.8785 0.4375 0.1294

[0106] 0.8785 0.4375 0.1294

[0107] 0.2312 0.2500 0.7267

[0108] 0.6250 0.7371 0.2339

[0109...

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Abstract

The invention relates to a grey clustering analysis method, comprising the steps of: (1) providing a clustering albetion function: selecting n clustering objects to obtain m clustering indexes and construct an n*m table; (2) inputting the clustering albetion function into a computer and getting into the algorithm of grey clustering analysis and evaluation, comprising: performing equalization nondimensionalization treatment to the clustering albetion; determining the grey type of each clustering index value of each clustering object; calculating the albetion weight function value of each grey type by an estimation method or interpolation method; demarcating a clustering weight grey matrix; and constructing a clustering matrix; and (3) performing grey evaluation according to the result of step (2). The method overcomes the defect of great influence caused by individual factor in single factor evaluation, reflects the influence of the evaluation factors in an all-round way, and has objective evaluation result, convenient and rapid calculation, accurate result, wide applicability, precise evaluation and high sensitivity.

Description

technical field [0001] The invention belongs to the field of system science and technology, and in particular relates to a gray clustering analysis method. Background technique [0002] The theory of gray clustering analysis is an independent new discipline of system science founded by Professor Deng Julong, a famous scholar in my country. Its research object is "small sample" and "poor information" uncertainty system with "partial information known and part unknown". It grasps the future operation and evolution law of the entire system by grasping "partial" known information. Because it can make an accurate and objective evaluation of the comprehensive performance of the system on the basis of limited information, it is suitable for many disciplines. However, due to the large amount of calculation, many complex mathematical problems are involved, and the personnel have high requirements for mathematical knowledge, this greatly limits the application of gray clustering ana...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F19/3431G16H50/30
Inventor 蔡再生陈玉梅丁志用杨斌姚建洲
Owner DONGHUA UNIV
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