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Self-adapting preferred fuzzy kernel clustering based naphtha attribute clustering method

A technology of fuzzy kernel clustering and clustering method is applied in the field of fuzzy kernel clustering for adaptively optimizing the number of clusters of naphtha attributes, which can solve the problem of low clustering accuracy, sensitivity to initial values, and limited application of fuzzy kernel clustering methods. And other issues

Inactive Publication Date: 2013-08-07
EAST CHINA UNIV OF SCI & TECH
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Problems solved by technology

However, the traditional fuzzy kernel clustering method requires an operator who is familiar with the process mechanism to give the number of clusters of naphtha attribute data in advance, and is sensitive to the initial value and has low clustering accuracy, which greatly limits the fuzzy kernel clustering method. Application in the actual process

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  • Self-adapting preferred fuzzy kernel clustering based naphtha attribute clustering method
  • Self-adapting preferred fuzzy kernel clustering based naphtha attribute clustering method
  • Self-adapting preferred fuzzy kernel clustering based naphtha attribute clustering method

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Embodiment Construction

[0051] Below in conjunction with accompanying drawing and example, further illustrate the present invention.

[0052] Step 1: Regularly analyze and organize the naphtha in the new and old areas of a petrochemical olefin plant. After data screening and processing, 170 sets of oil product data are obtained as the original data set for naphtha data clustering. Through mechanism analysis, the present invention selects the content of straight-chain alkanes (P+I) and the ratio of the mass content of normal alkanes to iso-alkanes (P / I) as the two attributes of clustering.

[0053] The second step: use the processed 170 sets of oil product data as the naphtha attribute data set, that is, X={x k |k=1,2,…,170}, x k =[x k1 ,x k2 ] for data x k The 2-dimensional feature vector of . Take the allowable error delt=0.00001, the maximum number of iterations t max =1000, fuzzy control index m=2, Gaussian kernel parameter σ=1.

[0054] The third step: select the initial cluster center by ...

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Abstract

The invention relates to a fuzzy kernel clustering method for self-adapting preferred naphtha attribute clustering numbers based on Gaussian nucleation validity indexes. The density and distance based initial clustering center selection method successfully solves the problems that fuzzy kernel clustering methods are sensitive to initial values, the operation speed is low and the implementing time is long. According to the method, a density measurement method is defined to select data objects with high densities to serve as initial clustering centers, the problem that the method is sensitive to initial values is effectively solved, and simultaneously, a two-dimensional array is set to store distances among naphtha attribute data, so that the calculation time is greatly shortened, and the clustering efficiency is improved.

Description

technical field [0001] The invention relates to a fuzzy kernel clustering method for processing naphtha attribute data in the industrial production process of ethylene cracking, in particular to a fuzzy kernel clustering method based on the Gaussian kernelization effectiveness index for adaptively optimizing the number of naphtha attribute clusters . Background technique [0002] Naphtha is a mixture of C4-C12 alkanes, cycloalkanes, aromatics, and olefins, and is currently the most widely used ethylene cracking raw material in the world. The cracking performance of naphtha cracking to ethylene is mainly affected by the following three aspects: raw material properties, cracking conditions, type and structure of cracking furnace. The raw material property is the most important internal factor affecting the cracking performance of ethylene. In the research, the naphtha attribute data are usually clustered, and the cluster centers of each category are extracted. The oil cracki...

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Application Information

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IPC IPC(8): G06F19/00
Inventor 钱锋王振雷梅华赵亮
Owner EAST CHINA UNIV OF SCI & TECH
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