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Coal mine water inflow prediction method and system based on LSTM algorithm

A water inflow and coal mine technology, applied in the fields of artificial intelligence and coal mining water disaster prevention, can solve the problem that the water inflow cannot be accurately predicted, and achieve the effect of ensuring safe mining

Inactive Publication Date: 2019-12-17
SHANDONG INSPUR GENESOFT INFORMATION TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The technical task of the present invention is to address the above deficiencies and provide a method and system for predicting coal mine water inflow based on the LSTM algorithm, which solves the problem that the water inflow in the coal mining sink cannot be accurately predicted in the existing coal mining water disaster prevention technology , can accurately and effectively predict the water inflow in the coal mining sink, and ensure the safe mining of coal

Method used

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  • Coal mine water inflow prediction method and system based on LSTM algorithm
  • Coal mine water inflow prediction method and system based on LSTM algorithm
  • Coal mine water inflow prediction method and system based on LSTM algorithm

Examples

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Effect test

Embodiment 1

[0052] A method for predicting coal mine water inflow based on LSTM algorithm, the method is realized through the following steps:

[0053] 1. Analyze and screen the relevant factors of coal mine water gushing to construct the coal mine water gushing characteristic matrix.

[0054] The factors related to coal mine water inrush include: thickness of aquifer, permeability coefficient of aquifer, hydraulic pressure of aquifer, water-richness of aquifer, thickness of effective aquifer, thickness of brittle rock on aquifer, thickness ratio of aquifer to effective aquifer , core collection rate, core drilling rate, the distance from the height of the water-conducting fracture zone to the bottom boundary of the water-filled aquifer, and structural fractures.

[0055] Factors related to water gushing in coal mines also include atmospheric rainfall, water level drawdown, daily mined-out area and cumulative area of ​​mined-out area, daily propelled mining length and total propelled leng...

Embodiment 2

[0068] A coal mine water inflow prediction system based on LSTM algorithm, including a data acquisition module, a data processing module, a model training module and a model evaluation module.

[0069] The data acquisition module is used to analyze and screen the relevant factors of coal mine water gushing to construct the coal mine water gushing characteristic matrix.

[0070] The coal mine water gushing related factors include: aquifer thickness, aquifer permeability coefficient, water pressure of aquifer, water richness of aquifer, thickness of effective aquifer, thickness of brittle rock on aquifer, thickness of aquifer and effective aquifer ratio, core collection rate, core drilling rate, distance from the height of the water-conducting fracture zone to the bottom of the water-filled aquifer, and structural fractures. As well as atmospheric rainfall, water level drawdown, daily mined-out area and cumulative area of ​​mined-out area, daily propelled mining length and total...

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Abstract

The invention discloses a coal mine water inflow prediction method and system based on an LSTM algorithm, and belongs to the technical field of artificial intelligence and coal mining water disaster prevention and control, and the method comprises the following steps: 1) analyzing and screening coal mine water inflow related factors to construct a coal mine water inflow characteristic matrix; 2) performing data processing on the coal mine water gushing characteristic matrix, wherein the data processing comprises characteristic matrix variable correlation screening and characteristic matrix variable normalization processing; 3) constructing a coal mine water inflow prediction model based on an LSTM algorithm, constructing an LSTM network structure, and training the prediction model, the LSTM network structure having a memory unit, an input gate, a forgetting gate and an output gate; 4) carrying out model prediction evaluation and model usage. According to the method, the problem that inan existing coal mining water disaster prevention and control technology, the water inflow in the coal mining sink cannot be accurately predicted is solved, the water inflow in the coal mining sink can be accurately and effectively predicted, and safe coal mining is guaranteed.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence and coal mining water disaster prevention and control, in particular to a method and system for predicting coal mine water inflow based on LSTM algorithm. Background technique [0002] Coal mine water gushing is one of the most common disasters that threaten mine safety in the process of mine construction and production, alongside mine gas and fire. In the process of coal mine construction and production, due to the complexity of mine hydrogeological conditions and the limitations of people's cognition of mine water filling elements, mine water disaster prevention and control measures are often not in place or other concealed water hazard conditions beyond people's ability to understand The existence of various types of mine water damage. [0003] At present, the commonly used coal mine water inflow prediction methods can be roughly classified into two categories: deterministic me...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q50/02G06Q10/04G06N3/04
CPCG06Q50/02G06Q10/04G06N3/044G06N3/045
Inventor 宗云兵
Owner SHANDONG INSPUR GENESOFT INFORMATION TECH CO LTD
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