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Periodic table of the elements in the perspective of artificial neural networks

机译:人工神经网络视角下的元素周期表

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摘要

Although several chemical elements were not known by end of the 18th century, Mendeleyev came up with an astonishing achievement: the periodic table of elements. He was not only able to predict the existence of (then) new elements but also to provide accurate estimates of their chemical and physical properties. This is certainly a relevant example of the human intelligence. Here, we intend to shed some light on the following question: Can an artificial intelligence system yield a classification of the elements that resembles, in some sense, the periodic table? To achieve our goal, we have fed a self-organized map (SOM) with information available at Mendeleyev's time. Our results show that similar elements tend to form individual clusters. Thus, SOM generates clusters of halogens, alkaline metals and transition metals that show a similarity with the periodic table of elements.
机译:尽管18世纪末尚不知道几种化学元素,但门捷列夫却取得了惊人的成就:元素周期表。他不仅能够预测(当时)新元素的存在,而且能够提供其化学和物理特性的准确估计。这无疑是人类智能的一个相关例子。在此,我们打算阐明以下问题:人工智能系统能否对元素周期进行分类,在某种意义上类似于元素周期表?为了实现我们的目标,我们在门捷列夫(Mendeleyev)时代提供了自组织地图(SOM)和可用信息。我们的结果表明,相似的元素倾向于形成单独的簇。因此,SOM生成的卤素,碱金属和过渡金属簇与元素周期表具有相似性。

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