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Study on the Screening of Active Components of Natural Products Based on Artificial intelligence

机译：基于人工智能的天然产物活性成分筛选研究

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摘要

With the worldwide research on natural product activity, new technologies and methods have been added to the screening of natural products. This effectively improves the efficiency and precision of the screening of the active ingredients of natural products. Artificial intelligence is a new technology which is currently in the field of computer, the basic principle of artificial intelligence technology was applied to the screening of active components of natural products in the paper, which has laid a solid theoretical foundation and support for strong screening active components in natural products. Different from the previous research methods, the method based on artificial intelligence not only promotes the role of biological activity, but also effectively shortens the time of discovery of active compounds[1]. The modern intelligent algorithm used in this article, and the full algorithm of support vector machine (SVM) classification performance and excellent precision of the genetic algorithm (GA) with high robustness of the comprehensive, premise analysis of the active components of natural products in quantity, build the basic framework of intelligent quantitative evaluation. We combined with the actual situation to verify the practicality of the mode in the subsequent learning process, which confirmed the feasibility of the model, to provide a basis and reference for the subsequent chemical treatment of natural products.
机译：随着全球对天然产品活动的研究，已添加新技术和方法在筛选天然产品中。这有效地提高了天然产物的活性成分的筛选效率和精度。人工智能是一种目前在计算机领域的新技术，人工智能技术的基本原理应用于筛查自然产品的活性成分，为奠定了坚实的理论基础和对强筛选活性的支持天然产品中的组件。与以前的研究方法不同，基于人工智能的方法不仅促进生物活性的作用，而且还有效地缩短了活性化合物的发现时间[1]。本文中使用的现代智能算法，以及全面的支持向量机（SVM）分类性能和优异的遗传算法精度（GA），具有高稳健性的全面，前提分析天然产物的有效成分数量，建立智能定量评估的基本框架。我们与实际情况相结合验证了随后的学习过程中模式的实用性，这证实了模型的可行性，为自然产品的后续化学处理提供了基础和参考。

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