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A Biologically Intelligent Encoding Approach to a Hierarchical Classification of Relational Elements in a Digraph

机译:有向图的关系元素分级分类的生物智能编码方法

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Parallel processing functions using molecules have advantages to be exploited for classifying the given relational elements in a digraph. For instance, hierarchical structural modelling is used for classifying complicated objects into a hierarchical structure. In this paper, we consider the example of a digraph of hierarchical structural modelling that can be transformed to sequences of molecules, and propose a biologically intelligent method of encoding molecular sequences of different types, through the hierarchical classification of hierarchical structural modelling. Moreover, we show that this innovative biologically intelligent encoding method can be applied, not only to hierarchical structural modelling, but also to other relational problems composed of elements from digraphs.
机译:使用分子的并行处理功能具有可用于对有向图中的给定关系元素进行分类的优势。例如,分层结构建模用于将复杂对象分类为分层结构。在本文中,我们以可以转换为分子序列的层次结构建模图的示例为例,并提出了一种通过对层次结构建模进行层次分类来对不同类型的分子序列进行编码的生物智能方法。此外,我们表明,这种创新的生物智能编码方法不仅可以应用于层次结构建模,而且可以应用于由二字组成的其他关系问题。

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