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:
Nov. 05, 2024

Filed:

Jun. 16, 2021
Applicants:

Chongqing University, Chongqing, CN;

North China Institute of Science and Technology, Beijing, CN;

Inventors:

Quanle Zou, Zhenping County, CN;

Zhiheng Cheng, Beijing, CN;

Liang Chen, Beijing, CN;

Hongbing Wang, Zhecheng County, CN;

Tengfei Ma, Qingfeng County, CN;

Zihan Chen, Chaozhou, CN;

Zhenli Zhang, Xinmi, CN;

Zhimin Wang, Chongqing, CN;

Ying Liu, Chongqing, CN;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 30/27 (2020.01); E21C 39/00 (2006.01); G06F 30/23 (2020.01); G06N 3/04 (2023.01); G06N 3/088 (2023.01); G06F 111/10 (2020.01);
U.S. Cl.
CPC ...
G06F 30/23 (2020.01); E21C 39/00 (2013.01); G06F 30/27 (2020.01); G06N 3/04 (2013.01); G06N 3/088 (2013.01); G06F 2111/10 (2020.01);
Abstract

A method for quickly optimizing key mining parameters of an outburst coal seam as provided includes steps of constructing a graphic basic information model of the coal mine, giving coal mine characteristic information, performing mining simulation, constructing a CNN-LSTM predicating model, obtaining changes under different mining conditions, constructing a Lorenz chaotic primer, and the like. The model can be improved with continuous breakthroughs in theory, so that the model has a strong learning ability and can adapt to the constantly changing complex geological environment. The method has very good predictability for the determination of coal seam group parameters, and can efficiently select and output a set of candidate parameters.


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