Evolutionary algorithms using a neural network like migration scheme.
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| Title: | Evolutionary algorithms using a neural network like migration scheme. |
|---|---|
| Authors: | Villmann, Thomas |
| Source: | Integrated Computer-Aided Engineering. 2002, Vol. 9 Issue 1, p25. 11p. |
| Subjects: | Algorithms, Artificial neural networks, Iterative methods (Mathematics) |
| Abstract: | We introduce a multiple subpopulation approach for parallel evolutionary algorithms the migration scheme of which follows a neural network learning like dynamic. It is adapted from the approach of collective learning in self-organizing maps with a more and more separation during time. We succesfully apply this approach to clustering real world data in psychotherapy research and VLSI-design. The advantages of the approach are shown which consist in a reduced communication overhead between the subpopulations preserving a non-vanishing information flow and an improved convergence rate resulting in decreasing computational costs. [ABSTRACT FROM AUTHOR] |
| Copyright of Integrated Computer-Aided Engineering is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: egs DbLabel: Engineering Source An: 5846225 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Evolutionary algorithms using a neural network like migration scheme. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Villmann%2C+Thomas%22">Villmann, Thomas</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Integrated+Computer-Aided+Engineering%22">Integrated Computer-Aided Engineering</searchLink>. 2002, Vol. 9 Issue 1, p25. 11p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Iterative+methods+%28Mathematics%29%22">Iterative methods (Mathematics)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: We introduce a multiple subpopulation approach for parallel evolutionary algorithms the migration scheme of which follows a neural network learning like dynamic. It is adapted from the approach of collective learning in self-organizing maps with a more and more separation during time. We succesfully apply this approach to clustering real world data in psychotherapy research and VLSI-design. The advantages of the approach are shown which consist in a reduced communication overhead between the subpopulations preserving a non-vanishing information flow and an improved convergence rate resulting in decreasing computational costs. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Integrated Computer-Aided Engineering is the property of Sage Publications Inc. and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3233/ICA-2002-9102 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 11 StartPage: 25 Subjects: – SubjectFull: Algorithms Type: general – SubjectFull: Artificial neural networks Type: general – SubjectFull: Iterative methods (Mathematics) Type: general Titles: – TitleFull: Evolutionary algorithms using a neural network like migration scheme. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Villmann, Thomas IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 03 Text: 2002 Type: published Y: 2002 Identifiers: – Type: issn-print Value: 10692509 Numbering: – Type: volume Value: 9 – Type: issue Value: 1 Titles: – TitleFull: Integrated Computer-Aided Engineering Type: main |
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