In general, most of the substances in nature exist in mixtures, and the noninvasive identification of mixture composition with high speed and accuracy remains a difficult task. However, the development of Raman spectroscopy, machine learning, and deep learning techniques has paved the way for achieving efficient analytical tools capable of identifying mixture components, thus leading to an apparent breakthrough in the identification of mixtures beyond traditional chemical analysis methods. This review summarizes the work of Raman spectroscopy in identifying the composition of substances; reviews the preprocessing process of Raman spectroscopy, artificial intelligence analysis methods, and analysis procedures; and examines the application of artificial intelligence. Finally, the advantages and disadvantages and development prospects of Raman spectroscopy are discussed in detail.

中文翻译：

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人工智能结合拉曼光谱识别物质成分的方法综述

一般来说，自然界中的大部分物质都存在于混合物中，快速、准确地对混合物成分进行无创识别仍然是一项艰巨的任务。然而，拉曼光谱、机器学习和深度学习技术的发展为实现能够识别混合物成分的高效分析工具铺平了道路，从而在混合物识别方面取得了明显突破，超越了传统的化学分析方法。这篇综述总结了拉曼光谱在识别物质成分方面的工作；回顾拉曼光谱的预处理过程、人工智能分析方法和分析程序；并检查人工智能的应用。最后，