A MIAÚ immár 25+ éve áll a Köz szolgálatára!
MATARKA-nézet
Üzenet az Olvasóhoz:
a MIAÚ virtuális hasábjain található gondolatokat
pl. Ramanudzsan feljegyzéseihez hasonlóan illik értelmezni (akarni):
a gondolatoknak a minősége/potenciálja az értékképző,
s nem az, hol jelennek meg ezek a gondolatok...
Ami másnak pl. a Facebook: MYX-team-hírek
(Utolsó módosítás: 2015.VII.19.14:08 - MIAÚ-RSS)
MEASURING HOMOGENEITY OF COUNTRIES IN THE EUROPEAN UNION BASED ON SIMILARITY ANALYSES (5. International Anatolian Scientific Research Congress July 21-23, 2023 / Hakkari, Türkiye)
Vezércikk: 2023. December (MIAU No. 304.)
(Előző cikk: MIAU No. 303.)
Keywords: homogeneity, similarity, modelling, OAM, data science, EU, artificial intelligence
Abstract:
Present status: Increasing integrity plays for the European Union a significant role since it was
established back in 1950. Also, it is to be found in the Single European Act where the article 130.a
defines Community shall develop and pursue its actions leading to the strengthening of its economic
and social cohesion (c.f. https://eur-lex.europa.eu/legalcontent/EN/TXT/PDF/?uri=CELEX:11986U/TXT).
To foster each country on cohesion/integrity, the leadership of the EU decides on millions of euros to be allocated and used for integration purposes.
Normally, these goals are also agreed on beforehand and it aligns with the future strategy of the
European Union.
To ensure that financial aid contributed accordingly across countries, there are numerous ways to
calculate the degree of integration, which were developed by well-known economists. These methods
are heavily relying on the GDP and the produced volume of buying and selling in a country rather than
focusing on the characteristics of the raw dataset in comparison to other countries.
Goals/Tasks: The aim of this study is to demonstrate a lot of alternative ways how the homogeneity of
European countries can be measured in a holistic and automated way, moving away from GDP- and
volume-based measuring, but taking the characteristics of time-series statistical data into consideration
in an objective way. The research needs to answer one main question among others: Can different
countries/regions of the EU have the same homogeneity index but in other way? Another important
goal is to validate and eliminate potential fake-news in online or written newspapers concerning
especially Hungary and Germany.
Solution: To assess raw data characteristics, five time-series data layers has been “randomly” extracted
from the OECD (The Organization for Economic Cooperation and Development) database and used
between 1995-2021 and includes 22 countries for the EU. These five layers are average yearly wages,
average yearly working hours, GDP, average life expectancy and unemployment rate. Additional
calculations e.g. averages, standard deviations, relative distances from averages has been calculated
for every year in order to build an OAM (Object-Attribute-Matrix) as the input database for COCO Y0
(c.f. https://miau.my-x.hu/myx-free/index.php3?x=e091).
Conclusions: During the naive analysis approach (where no artificial intelligence is included for
optimizing the objectivity) it is close to impossible to deliver a ranking between countries due to the
high number of considerable effects (over 550 graphs) of raw data characteristics. With using our
artificial intelligence solution for antidiscrimination models, it is possible to form rankings between
countries and regions objectively and with that our algorithm can function as decision making
programme for the EU.
In terms of countries which joined the EU in 2004, we identified that Hungary homogenised the least,
meanwhile Slovenia made the most efforts based on the characteristics of their statistical data.
Together with all examined 22 EU countries Hungary is on the 17th place meanwhile Slovenia is the
number one of the ranking. Based on this, it can be said that those countries which joined the EU back
in 2004, has made extremely different pathways objectively.
Regarding homogeneity, the essay thus presents coexisting, possible interpretations, where individual
interpretation is always riskier than the application of a collective hermeneutic interpretation which
aims for consistency.
Also, there is no official definition of homogeneity as per nowadays as there is no clear
(mathematical/algorithmic) definition of homogeneity. Nowhere is there a “fever curve” showing the
dynamics of homogeneity for different country and the EU as such, i.e. the EU has not yet reached the
level of cybernetics that works with dashboards like a spaceship.
(Tovább - DOC)
***
(Tovább - PDF)
Észrevételeit érdeklődéssel várjuk email-ben!
((Vissza))
miau.my-x.hu
myxfree.tool
rss.services
]
