Controlling The Problem Of Bloating Using Stepwise Crossover And Double Mutation Technique
Created by W.Langdon from
gp-bibliography.bib Revision:1.8081
- @Article{Bhardwaj:2011:ACIJ,
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author = "Arpit Bhardwaj and Aditi Sakalle and
Harshita Chouhan and Harshit Bhardwaj",
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title = "Controlling The Problem Of Bloating Using Stepwise
Crossover And Double Mutation Technique",
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year = "2011",
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journal = "Advanced Computing : an International Journal",
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volume = "2",
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number = "6",
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pages = "59--68",
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month = nov,
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publisher = "Academy \& Industry Research Collaboration Center
(AIRCC)",
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keywords = "genetic algorithms, genetic programming, bloat,
stepwise crossover, double mutation, elitism, fitness,
Java, Oracle 10g",
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ISSN = "2229726X",
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URL = "http://airccse.org/journal/acij/papers/1111acij06.pdf",
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broken = "http://www.doaj.org/doaj?func=openurl\&genre=article\&issn=2229726X\&date=2011\&volume=2\&issue=6\&spage=59",
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DOI = "doi:10.5121/acij.2011.2606",
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size = "10 pages",
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abstract = "During the evolution of solutions using genetic
programming (GP) there is generally an increase in
average tree size without a corresponding increase in
fitness---a phenomenon commonly referred to as bloat.
The conception of bloat in Genetic Programming is a
well naturalised phenomenon characterised by
variable-length genomes gradually maturating in size
during evolution. 'In a very real sense, bloating makes
genetic programming a race against time, to find the
best solution possible before bloat puts an effective
stop to the search.' In this paper we are proposing a
Stepwise crossover and double mutation operation in
order to reduce the bloat. In this especial crossover
operation we are using local elitism replacement in
combination with depth limit and size of the trees to
reduce the problem of bloat substantially without
compromising the performance. The use of local elitism
in crossover and mutation increases the accuracy of the
operation and also reduces the problem of bloat and
further improves the performance. To shew our approach
we have designed a Multiclass Classifier using GP by
taking few benchmark datasets.",
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notes = "IRIS, WBC, BUPA, WINE, ABALONE, SPOKEN ARABIC DIGIT,
HILL-VALLEY",
-
bibsource = "OAI-PMH server at www.doaj.org",
-
oai = "oai:doaj-articles:4e07bf6e3c343d42b02de6aed48a4d17",
- }
Genetic Programming entries for
Arpit Bhardwaj
Aditi Sakalle
Harshita Chouhan
Harshit Bhardwaj
Citations