On the parallelization of artificial neural networks and genetic algorithms

Adamidis, Panagiotis/ Petridis, Vassilios/ Αδαμίδης, Παναγιώτης/ Πετρίδης, Βασίλειος


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dc.contributor.authorAdamidis, Panagiotisel
dc.contributor.authorPetridis, Vassiliosel
dc.contributor.otherΑδαμίδης, Παναγιώτηςel
dc.contributor.otherΠετρίδης, Βασίλειοςel
dc.date.accessioned2015-07-21T11:11:21Zel
dc.date.accessioned2018-02-28T17:06:00Z-
dc.date.available2015-07-21T11:11:21Zel
dc.date.available2018-02-28T17:06:00Z-
dc.date.issued1998el
dc.identifierhttp://www.tandfonline.com/doi/abs/10.1080/00207169808804654?journalCode=gcom20#.Va4ki6Ttmkoel
dc.identifier10.1080/00207169808804654el
dc.identifier.citationJournal: International Journal of Computer Mathematics, vol.67, no.1-2, 1998el
dc.identifier.citationAdamidis, P. & Petridis, V. (1998). On the parallelization of artificial neural networks and genetic algorithms. International Journal of Computer Mathematics. 67(1-2):105-125.el
dc.identifier.issn0020-7160el
dc.identifier.issn1029-0265el
dc.identifier.urihttp://195.251.240.227/jspui/handle/123456789/10371-
dc.descriptionΔημοσιεύσεις μελών--ΣΤΕΦ--Τμήμα Μηχανικών Πληροφορικής, 1998el
dc.description.abstractSimulating an ANN or a genetic algorithm on a parallel processing system one can use several techniques. This paper presents two methods on implementing parallel simulations of Artificial Neural Networks (ANNs) on Transputer Based Systems, using the C programming language under Helios O.S. and Component Distribution Language (CDL) or, alternatively, the 3L Parallel C language. The Processor Farm topology is used for the parallel implementation of Back-Propagation and Multi-Layered Feed-Forward ANNs. A transputer system was also used to implement a simulation of an island parallel genetic algorithm (PGA) and a new optimization method based on PGAs. The method, called Co-operating Populations with Different Evolution Behaviours (CoPDEB), is independent of the machine architecture. It allows the populations to exhibit different evolution behaviours by using a variety of selection mechanisms, operators, communication methods, and parameters as explained in the sequel.el
dc.language.isoenel
dc.publisherTaylor & Francisel
dc.rightsThis item is probably protected by Copyright Legislationel
dc.rightsΤο τεκμήριο πιθανώς υπόκειται σε σχετική με τα Πνευματικά Δικαιώματα νομοθεσίαel
dc.source.urihttp://www.tandfonline.com/toc/gcom20/67/1-2#.Va4lKKTtmkoel
dc.subjectParallelizationel
dc.subjectNeural networksel
dc.subjectGenetic algorithmsel
dc.subjectCo-operating populationsel
dc.subjectDifferent evolution behavioursel
dc.subjectC.1.2el
dc.subjectI.2.6el
dc.subjectC.1.3el
dc.titleOn the parallelization of artificial neural networks and genetic algorithmsel
dc.typeArticleel
heal.typeotherel
heal.type.enOtheren
heal.dateAvailable2018-02-28T17:07:00Z-
heal.languageelel
heal.accessfreeel
heal.recordProviderΤΕΙ Θεσσαλονίκηςel
heal.fullTextAvailabilityfalseel
heal.type.elΆλλοel
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