Yılmaz, Meriç

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https://hdl.handle.net/20.500.14411/6689
Name Variants
M., Yilmaz
Yilmaz M.
Yilmaz,M.
Y.,Meric
Selamoglu M.
Meric, Yilmaz
Yilmaz, Meric
Y., Meriç
M., Yılmaz
Meriç Yılmaz
Apaydin M.
Meriç, Yılmaz
Yilmaz,Meric
Y.,Meriç
Yılmaz, Meriç
M.,Yilmaz
Yılmaz,M.
M.,Yılmaz
Y., Meric
Job Title
Doçent Doktor
Email Address
meric.yilmaz@atilim.edu.tr
Main Affiliation
Civil Engineering
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Website
ORCID ID
0000-0001-6921-7687
Scopus Author ID
57214083722
Turkish CoHE Profile ID
99A550748996DD77
Google Scholar ID
3p-1_IIAAAAJ
WoS Researcher ID
G-5145-2017

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233

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10

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5

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132

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181

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13.20

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18.10

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Communications in Computer and Information Science -- 29th European Systems, Software and Services Process Improvement, EuroSPI 2022 -- 31 August 2022 through 2 September 2022 -- Salzburg -- 2824491
Doğal Afetler ve Çevre Dergisi1
Environmental Science and Pollution Research1
Journal of Applied Water Engineering and Research1
Journal of the Croatian Association of Civil Engineers1
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Now showing 1 - 2 of 2
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    Citation - Scopus: 21
    Examining the Use of Non-Fungible Tokens (nfts) as a Trading Mechanism for the Metaverse
    (Springer Science and Business Media Deutschland GmbH, 2022) Yilmaz,M.; Hacaloğlu,T.; Clarke,P.
    The notion of a metaverse seems hard to define but encourages the impression that it can be considered as a new virtual metaphysical landscape that somehow goes beyond our geographical locations and understanding (i.e., independent of time and space). Based on virtual reality, augmented reality, and blockchain, it is envisioned as an independent but extended world that is planned to be a digital virtuality entrenched not only in our old habits such as gaming and entertainment but also in virtual asset trade. In particular, trading is a pillar of the virtual economy, and auction houses will be crucial for Metaverse trading. This exploratory study examines the possibility of using an auction environment to improve the trading capabilities in a virtual universe. We investigate the cases of creating a virtual auction house with the potential of social trading of virtual assets with crypto coins and bartering. To this end, we built a virtual auction house and tested it initially using a set of scenarios. Our preliminary findings suggest that creating a virtual trading environment would be beneficial as an environment for buying and selling virtual assets and exploring their consequences. © 2022, Springer Nature Switzerland AG.
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    Forecasting Direction of Bist 100 Index: an Integrated Machine Learning Approach
    (Springer Science and Business Media B.V., 2021) Ünlü,K.D.; Potas,N.; Yılmaz,M.
    In recent years trends in analyzing and forecasting financial time series moves from classical Box-Jenkins methodology to machine learning algorithms because of the non-linearity and non-stationary of the time series. In this study, we employed a machine learning algorithm called support vector machine to predict the daily price direction of BIST 100 index. In addition, we use random forest algorithm for feature selection and showed that by removing some features from the model, performance of the model increases. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.