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

Authors:
Ikno Kim;Junzo Watada
Affiliations:
Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan 808-0135;Graduate School of Information, Production and Systems, Waseda University, Kitakyushu, Japan 808-0135
Venue:
KES '09 Proceedings of the 13th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems: Part II
Year:
2009

Citing 3
Cited 0

Molecular computation of solutions to combinatorial problems

Science
Bio-soft computing with fixed-length DNA to a group control optimization problem

Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on BISCSE 2005 " Forging the Frontiers" Part II
DNA Computing and Its Applications

ISDA '08 Proceedings of the 2008 Eighth International Conference on Intelligent Systems Design and Applications - Volume 02

Quantified Score

Hi-index	0.00

Visualization

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.