使用富里埃变换红外光谱法估计煤炭灰产量的多模型方法
Sameeksha Mishra1, Anup K Prasad2,3, Arya Vinod1
1Photogeology and Image Processing Laboratory, Department of Applied Geology, Indian Institute of Technology (Indian School of Mines), Dhanbad, 826004, India.
Scientific reports
|April 21, 2025
概括
福里埃变换红外光谱 (FTIR) 为预测煤灰产量提供了一种快速的方法,克服了传统近距离分析的局限性. 使用FTIR数据的多模型估计方法为煤炭质量评估提供了准确和可靠的结果.
科学领域:
- 分析化学 分析化学
- 频谱学是一种光谱学.
- 材料科学 材料科学 材料科学
背景情况:
- 煤灰产量是影响商业评级和工业应用的关键质量指标.
- 传统的近距离分析以确定灰产量是耗时和劳动密集的.
- 开发快速,准确的灰产预测方法对于煤炭行业至关重要.
研究的目的:
- 提出一种新的方法来预测煤灰产量,使用中红外里埃变换红外光谱法 (FTIR).
- 评估各种回归算法的性能,以预测灰产量.
- 引入多模型估计 (MME) 策略,以提高准确性和可靠性.
主要方法:
- 利用中红外FTIR光谱数据 (1450-350厘米−1) 来识别光谱敏感的吸收波段.
- 应用了多重回归算法:零碎线性回归 (PLR),人工神经网络 (ANN),部分最小平方回归 (PLSR),支持向量回归 (SVR) 和随机森林 (RF).
- 实施了多模型估计 (MME) 方法,以预测最好的三个模型 (PLR,PLSR,ANN) 的平均值.
主要成果:
- 采用MME方法实现了0.883的高确定系数 (R2),优于单个模型.
- 对于MME的关键绩效指标包括RMSE的3.059重%,RMSE%的30.080,MBE%的3.694,和MAE的2.249重%.
- 统计测试 (t-测试和F-测试) 证实FTIR衍生和近距离分析衍生灰产量之间没有显著差异.
结论:
- 与MME相结合的FTIR光谱学提供了一种准确而可靠的方法来预测煤灰产量.
- 这种基于FTIR的模型是一种可行的工业工具,用于快速评估煤炭质量,在Johilla Coalfield的样本上证明了这一点.
- 通过结合来自全球不同煤矿盆地的FTIR数据,可以实现进一步的改进.
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