基于卷积变化自编码器模型的紫外线光谱转移,用于检测河流中的化学氧气需求
Duo Zhang1,2, Hongyi Bai1,2, Laijun Sun1,2
1College of Electronics and Engineering, Heilongjiang University, Harbin 150080, China. 2221806@s.hlju.edu.cn.
Analytical methods : advancing methods and applications
|March 4, 2025
概括
这项研究引入了一种新的卷积变异自编码器 (CVAE) 方法,用于解决化学氧需求 (COD) 检测中的光谱数据转移. CVAE有效地在不同紫外线仪器之间传输光谱数据,改善模型共享和准确性.
科学领域:
- 环境科学 环境科学
- 分析化学 分析化学
- 频谱学是一种光谱学.
背景情况:
- 不同紫外线仪器之间的光谱数据转移阻碍了在河流中精确检测化学氧需求 (COD).
- 现有的预测模型经常由于仪器特定的光谱变化而失败.
研究的目的:
- 开发一种非线性光谱传输方法,以克服在不同紫外线仪器之间共享预测模型的挑战.
- 提高COD检测在河水分析中的准确性和可靠性.
主要方法:
- 卷积变异自编码器 (CVAE) 用于非线性光谱传输.
- CVAE使用编码器-解码器架构来提取关键的光谱特征并重建数据.
- 变异推理被纳入模型数据分布和捕获全球光谱特征.
主要成果:
- 与传统方法 (光谱空间转换,分片直接标准化,深度自编码器和卷积自编码器) 相比,拟议的CVAE方法显著降低了预测的根平均平方误差.
- 与比较方法相比,CVAE实现了1.0242,0.4571,0.4201和0.1965的预测误差减少.
- 该方法有效地解决了不同测量设备之间的模型共享问题.
结论:
- 基于CVAE的光谱转移方法为仪器独立的COD预测提供了强大的解决方案.
- 这种方法提高了预测模型在环境监测和水质评估中的适用性.
- 该研究为分析化学中的光谱数据处理和多变量校准提供了新的见解.
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