On the parallelization of artificial neural networks and genetic algorithms
Adamidis, Panagiotis/ Petridis, Vassilios/ Αδαμίδης, Παναγιώτης/ Πετρίδης, Βασίλειος
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Adamidis, Panagiotis | el |
dc.contributor.author | Petridis, Vassilios | el |
dc.contributor.other | Αδαμίδης, Παναγιώτης | el |
dc.contributor.other | Πετρίδης, Βασίλειος | el |
dc.date.accessioned | 2015-07-21T11:11:21Z | el |
dc.date.accessioned | 2018-02-28T17:06:00Z | - |
dc.date.available | 2015-07-21T11:11:21Z | el |
dc.date.available | 2018-02-28T17:06:00Z | - |
dc.date.issued | 1998 | el |
dc.identifier | http://www.tandfonline.com/doi/abs/10.1080/00207169808804654?journalCode=gcom20#.Va4ki6Ttmko | el |
dc.identifier | 10.1080/00207169808804654 | el |
dc.identifier.citation | Journal: International Journal of Computer Mathematics, vol.67, no.1-2, 1998 | el |
dc.identifier.citation | Adamidis, 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.issn | 0020-7160 | el |
dc.identifier.issn | 1029-0265 | el |
dc.identifier.uri | http://195.251.240.227/jspui/handle/123456789/10371 | - |
dc.description | Δημοσιεύσεις μελών--ΣΤΕΦ--Τμήμα Μηχανικών Πληροφορικής, 1998 | el |
dc.description.abstract | Simulating 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.iso | en | el |
dc.publisher | Taylor & Francis | el |
dc.rights | This item is probably protected by Copyright Legislation | el |
dc.rights | Το τεκμήριο πιθανώς υπόκειται σε σχετική με τα Πνευματικά Δικαιώματα νομοθεσία | el |
dc.source.uri | http://www.tandfonline.com/toc/gcom20/67/1-2#.Va4lKKTtmko | el |
dc.subject | Parallelization | el |
dc.subject | Neural networks | el |
dc.subject | Genetic algorithms | el |
dc.subject | Co-operating populations | el |
dc.subject | Different evolution behaviours | el |
dc.subject | C.1.2 | el |
dc.subject | I.2.6 | el |
dc.subject | C.1.3 | el |
dc.title | On the parallelization of artificial neural networks and genetic algorithms | el |
dc.type | Article | el |
heal.type | other | el |
heal.type.en | Other | en |
heal.dateAvailable | 2018-02-28T17:07:00Z | - |
heal.language | el | el |
heal.access | free | el |
heal.recordProvider | ΤΕΙ Θεσσαλονίκης | el |
heal.fullTextAvailability | false | el |
heal.type.el | Άλλο | el |
Appears in Collections: | Δημοσιεύσεις σε Περιοδικά |
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http://195.251.240.227/jspui/handle/123456789/10371
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