相关实验视频

Updated: Jun 7, 2025

A Uniaxial Compression Experiment with CO2-Bearing Coal Using a Visualized and Constant-Volume Gas-Solid Coupling Test System
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A Uniaxial Compression Experiment with CO2-Bearing Coal Using a Visualized and Constant-Volume Gas-Solid Coupling Test System

Published on: June 12, 2019

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先进的机器学习方案用于预测地下煤炭火灾地区的基于CO2流量的实验方法

Yongjun Wang1, Mingze Guo2, Hung Vo Thanh3

  • 1College of Safety Science and Engineering, Liaoning Technical University, Huludao 125105, China; Institute of Engineering and Environment, Liaoning Technical University, Huludao 125105, China; Key Laboratory of Mine Thermodynamic Disasters and Control of Ministry of Education, Huludao 125105, China.

Journal of advanced research
|November 9, 2024
PubMed
概括

这项研究开发了先进的机器学习模型,以准确预测来自地下煤炭火灾的表面二氧化碳 (CO2) 流量. 自然梯度增强回归 (NGRB) 模型显示出最佳性能,有助于环境监测和缓解.

关键词:
碳化合物 (CO) 的二氧化碳流量.气候变化 气候变化 气候变化环境监测环境监测环境监测自然梯度增加了回归的速度.地下煤炭火灾的发生

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