研究基于灰色系统理论的气体排放预测模型
Liyang Bai1,2, Hui Geng3, Guangming Yu4
1School of Civil Engineering, Qingdao University of Technology, Qingdao, 266033, China. 786661009@qq.com.
Scientific reports
|July 2, 2025
概括
准确预测采矿面气体排放对于安全和效率至关重要. 与传统方法相比,一种新的灰色预测模型 (GM (0,12)) 显著提高了预测准确性.
科学领域:
- 采矿工程 采矿工程 采矿工程
- 环境科学 环境科学
- 数据科学数据科学数据科学
背景情况:
- 准确的气体排放预测对于预防事故,优化采矿计划和确保可持续的煤矿开发至关重要.
- 现有的预测方法可能缺乏有效的矿山安全管理所需的精度.
研究的目的:
- 开发和验证一个非常准确的气体排放量预测模型,用于采矿面部.
- 通过改进气体排放预测,提高煤炭开采业务的安全性,效率和环境可持续性.
主要方法:
- 一个基于灰色系统理论的灰色预测模型被开发出来.
- 使用灰色相关性分析来识别和权衡关键影响因素 (例如气体含量,深度,厚度).
- 将GM (0,12) 模型与现场数据进行验证,并与多重线性回归进行比较.
主要成果:
- 煤层气体含量,厚度,采矿强度,深度和相邻的气体含量被确定为影响气体排放的最重要因素.
- 转基因 (0,12) 模型表现出极好的准确性,相对误差为0.799%.
- 转基因 (0,12) 模型显著超过了多重线性回归模型 (3.643%的相对误差).
结论:
- 拟议的GM (0,12) 模型为预测采矿面上的气体排放量提供了卓越的准确性.
- 这种先进的预测能力支持更安全,更有效,更绿色的煤炭开采实践.
- 灰色系统理论方法为解决采矿行业中复杂的环境预测挑战提供了一个强大的框架.
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