The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jul. 23, 2024

Filed:

Oct. 13, 2022
Applicant:

Guangdong University of Petrochemical Technology, Maoming, CN;

Inventors:

Shaolin Hu, Maoming, CN;

Qiliang Guo, Maoming, CN;

Qinghua Zhang, Maoming, CN;

Guo Xie, Maoming, CN;

Chenglin Wen, Maoming, CN;

Wenzhuo Chen, Maoming, CN;

Gaowei Lei, Maoming, CN;

Ye Ke, Maoming, CN;

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/28 (2019.01); G06F 16/22 (2019.01); G06F 16/2458 (2019.01);
U.S. Cl.
CPC ...
G06F 16/285 (2019.01); G06F 16/221 (2019.01); G06F 16/2462 (2019.01); G06F 16/2465 (2019.01);
Abstract

Disclosed is an autonomous mining method of industrial big data based on model sets, which comprises the following steps: S, building model sets and a mining engine based on domain knowledge and structural characteristics of multi-source heterogeneous data; S, carrying out data sampling on the multi-source heterogeneous data, and counting the fault-tolerant estimation of random error variance; S, mining data sets by using the mining engine, and determining the optimal fault-tolerant model of each sampled data sequence and the optimal fault-tolerant estimation of model parameters; S, performing goodness-of-fit statistics calculation and VV&A test by using the optimal fault-tolerant model; S, acquiring data model representation and connotation knowledge based on model clustering. The method can realize the automation of the mining process of big data, the integration of associated knowledge, the expansion of model sets, the integration of mining and modeling and the optimization of mining results.


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