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Applications of Rough Genetic Algorithms
Author(s) -
Lingras Pawan,
Davies Cedric
Publication year - 2001
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/0824-7935.00156
Subject(s) - rough set , genetic algorithm , generalization , interval (graph theory) , algorithm , computer science , quality control and genetic algorithms , artificial intelligence , data mining , mathematics , machine learning , meta optimization , combinatorics , mathematical analysis
This paper describes rough genetic algorithms based on the notion of interval values. A gene in a rough genetic algorithm can be represented using an interval. The paper explains how this generalization facilitates development of new genetic operators and evaluation measures. Various operations of rough genetic algorithms are illustrated using a simple document retrieval example. An experiment involving classification of interval‐valued traffic patterns demonstrates the usefulness of rough genetic algorithms for real‐world applications. A discussion on further extensions of rough genetic algorithms to rough sets is also included.