Konferans bildirisi Açık Erişim
Takci Mehmet Turker; Gözel Tuba; Hocaoglu Mehmet Hakan
<?xml version='1.0' encoding='UTF-8'?> <record xmlns="http://www.loc.gov/MARC21/slim"> <leader>00000nam##2200000uu#4500</leader> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Gözel Tuba</subfield> <subfield code="u">Gebze Teknik Üniversitesi</subfield> <subfield code="0">(orcid)0000-0003-4798-0635</subfield> </datafield> <datafield tag="700" ind1=" " ind2=" "> <subfield code="a">Hocaoglu Mehmet Hakan</subfield> <subfield code="u">Gebze Teknik Üniversitesi</subfield> <subfield code="0">(orcid)0000-0001-6528-3812</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Regression Analysis</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Artificial Neural Network</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Power Consumption Forecasting</subfield> </datafield> <datafield tag="653" ind1=" " ind2=" "> <subfield code="a">Data Center</subfield> </datafield> <datafield tag="980" ind1=" " ind2=" "> <subfield code="a">publication</subfield> <subfield code="b">conferencepaper</subfield> </datafield> <datafield tag="542" ind1=" " ind2=" "> <subfield code="l">open</subfield> </datafield> <datafield tag="041" ind1=" " ind2=" "> <subfield code="a">eng</subfield> </datafield> <datafield tag="856" ind1="4" ind2=" "> <subfield code="u">https://aperta.ulakbim.gov.trrecord/252117/files/54_2019_ISAP.pdf</subfield> <subfield code="z">md5:cf2ade577fa9606f8d78cfe42506aa05</subfield> <subfield code="s">899817</subfield> </datafield> <datafield tag="540" ind1=" " ind2=" "> <subfield code="a">Creative Commons Attribution Share-Alike</subfield> <subfield code="u">http://www.opendefinition.org/licenses/cc-by-sa</subfield> </datafield> <controlfield tag="005">20221211084945.0</controlfield> <controlfield tag="001">252117</controlfield> <datafield tag="520" ind1=" " ind2=" "> <subfield code="a"><p>In recent years, estimation algorithms become more popular in terms of forecasting customer behavior or any required data<br> for IT companies. Forecasting results can be used in different purposes such as improving the quality and capacity of production and<br> services, reducing to greenhouse gas emissions, and minimizing the power consumption. The accurate forecasting results are also beneficial for data centers which are the significant participants in the electricity market in terms of consuming huge power demand and have a chance to reduce consumed power, electricity costs by rescheduling their flexible loads for the future period. In this paper, power-consuming devices and variables affecting power consumption are explained. Also, the brief information about artificial neural network and regression analysis methods has been provided. The power consumption of Information Technology devices is forecasted by nonlinear regression analysis and artificial neural network methods. The forecasting results show that artificial neural<br> network method is more successful.</p></subfield> </datafield> <datafield tag="245" ind1=" " ind2=" "> <subfield code="a">Forecasting Power Consumption of IT Devices in a Data Center</subfield> </datafield> <datafield tag="100" ind1=" " ind2=" "> <subfield code="a">Takci Mehmet Turker</subfield> <subfield code="u">Gebze Teknik Üniversitesi</subfield> <subfield code="0">(orcid)0000-0002-5417-6621</subfield> </datafield> <datafield tag="909" ind1="C" ind2="O"> <subfield code="o">oai:aperta.ulakbim.gov.tr:252117</subfield> </datafield> <datafield tag="024" ind1=" " ind2=" "> <subfield code="a">10.1109/ISAP48318.2019.9065937</subfield> <subfield code="2">doi</subfield> </datafield> <datafield tag="260" ind1=" " ind2=" "> <subfield code="c">2019-12-10</subfield> </datafield> <datafield tag="650" ind1="1" ind2="7"> <subfield code="2">opendefinition.org</subfield> <subfield code="a">cc-by</subfield> </datafield> </record>
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