Ultraviolet visible spectral water chemical oxygen demand detection method based on two deep neural network model

IF 1.1 4区化学 Q3 SPECTROSCOPY Spectroscopy Letters Pub Date : 2024-08-28 DOI:10.1080/00387010.2024.2395326

Xiaojun Zhang, Yiwen Cai, Feng Wang, Jin Wu, Xiaoyu Liu

引用次数: 0

Abstract

Water resources are precious resources around the world, but pollution is becoming increasingly severe. While the degree of damage to water caused by organic pollutants is reflected by chemical oxy...

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基于两个深度神经网络模型的紫外可见光谱水化学需氧量检测方法

水资源是全世界的宝贵资源，但污染却日益严重。虽然有机污染物对水的破坏程度可以通过化学氧化剂和生物降解剂反映出来，但这些物质对水的破坏程度却很低。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Spectroscopy Letters 物理-光谱学

CiteScore

2.90

自引率

5.90%

发文量

审稿时长

1.3 months

期刊介绍： Spectroscopy Letters provides vital coverage of all types of spectroscopy across all the disciplines where they are used—including novel work in fundamental spectroscopy, applications, diagnostics and instrumentation. The audience is intended to be all practicing spectroscopists across all scientific (and some engineering) disciplines, including: physics, chemistry, biology, instrumentation science, and pharmaceutical science.

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