A biologically intelligent encoding approach to a hierarchical classification of relational elements in a digraph

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Abstract

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. © 2009 Springer Berlin Heidelberg.

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APA

Kim, I., & Watada, J. (2009). A biologically intelligent encoding approach to a hierarchical classification of relational elements in a digraph. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5712 LNAI, pp. 174–180). https://doi.org/10.1007/978-3-642-04592-9_22

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