Please use this identifier to cite or link to this item:
https://hdl.handle.net/20.500.14279/4131
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Zombanakis, George A. | - |
dc.contributor.author | Andreou, Andreas S. | - |
dc.date | 2011 | en |
dc.date.accessioned | 2014-07-09T07:04:27Z | - |
dc.date.accessioned | 2015-12-09T11:30:26Z | - |
dc.date.available | 2014-07-09T07:04:27Z | - |
dc.date.available | 2015-12-09T11:30:26Z | - |
dc.date.issued | 2011-08 | - |
dc.identifier | 1024-2694 | en |
dc.identifier.citation | Defence and Peace Economics, 2011, vol. 22, no. 4, pp. 459-469 | en_US |
dc.identifier.issn | 14768267 | - |
dc.identifier.uri | https://hdl.handle.net/20.500.14279/4131 | - |
dc.description.abstract | This paper looks into the Greek-Turkish arms race a decade after an earlier contribution to the issue that relied heavily on artificial neural networks. The time period between the two papers contributes to the reliability of the results derived, not just by increasing the number of observations, but also mainly by incorporating the progress made in the realm of artificial intelligence. The focus on the case of both countries unlike the paper mentioned above that dealt with just the Greek side provides ample room for comparative purposes regarding the determinants of defense expenditure on both sides. The results derived in terms of input significance estimation support the findings of the earlier research as indicated above, pointing to the leading role of the demographic preponderance of Turkey over Greece. The paper also points to the fact that 10 years later, Turkey continues to set the arms race rules against its rival by determining the defense expenditure of Greece, whereas the role of the latter in affecting the military spending of Turkey is non-existent. | en_US |
dc.format | en_US | |
dc.language | en | en |
dc.language.iso | en | en_US |
dc.relation.ispartof | Defence and Peace Economics | en_US |
dc.rights | © Taylor & Francis | en_US |
dc.subject | Arms race | en_US |
dc.subject | Neural networks | en_US |
dc.subject | Turkey | en_US |
dc.subject | Greece | en_US |
dc.title | Financial versus human resources in the Greek-Turkish arms race 10 years on: A forecasting investigation using artificial neural networks | en_US |
dc.type | Article | en_US |
dc.collaboration | Cyprus University of Technology | en_US |
dc.collaboration | Bank of Greece | en_US |
dc.subject.category | Electrical Engineering - Electronic Engineering - Information Engineering | en_US |
dc.journals | Subscription | en_US |
dc.review | Peer Reviewed | - |
dc.country | Cyprus | en_US |
dc.country | Greece | en_US |
dc.subject.field | Engineering and Technology | en_US |
dc.publication | Peer Reviewed | en_US |
dc.identifier.doi | 10.1080/10242694.2010.539858 | en_US |
dc.dept.handle | 123456789/134 | en |
dc.relation.issue | 4 | en_US |
dc.relation.volume | 22 | en_US |
cut.common.academicyear | 2011-2012 | en_US |
dc.identifier.spage | 459 | en_US |
dc.identifier.epage | 469 | en_US |
item.grantfulltext | none | - |
item.openairecristype | http://purl.org/coar/resource_type/c_6501 | - |
item.fulltext | No Fulltext | - |
item.languageiso639-1 | en | - |
item.cerifentitytype | Publications | - |
item.openairetype | article | - |
crisitem.journal.journalissn | 1476-8267 | - |
crisitem.journal.publisher | Taylor & Francis | - |
crisitem.author.dept | Department of Electrical Engineering, Computer Engineering and Informatics | - |
crisitem.author.faculty | Faculty of Engineering and Technology | - |
crisitem.author.orcid | 0000-0001-7104-2097 | - |
crisitem.author.parentorg | Faculty of Engineering and Technology | - |
Appears in Collections: | Άρθρα/Articles |
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