Browsing by Author "Yucekaya, A.D."

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Citation - Scopus: 0
A Comparative Application of Machine Learning Approaches To Win-Back Lost Customers
(Institute of Electrical and Electronics Engineers Inc., 2023) Yildirim, S.; Hekimoğlu, Mustafa; Yucekaya, A.D.; Hekimoglu, M.; Ozcan, B.
Today's consumer is more knowledgeable and conscious than in the past. For this reason, it is quite possible for consumers to leave their service/product providers and start receiving service from another service/product provider. Without a recovery strategy, companies often do not target their lost disloyal customer portfolio correctly and encounter the problem of lost customers. Lost customers can cause loss both in economic terms and in terms of business potential. At the same time, lost customers can also be considered as profits given to rival companies. What if the companies could foresee lost customers who would not want to receive service from them again? Could companies win back their customers? At this point, the article proposes using machine learning methods to recover lost customers for service providers. The customers that are likely to be lost in the future are estimated using the article's past stories of an automotive company's lost customers. The data used is completely real. LGBM, XGBoost, and Random Forest methods were used to estimate lost customers. Finally, the authors select the machine learning with the highest predictive success for customer recovery and discuss why this method might have worked well. © 2023 IEEE.
Citation - Scopus: 1
Genesys-Mod Turkey: Quantitative Scenarios for Low Carbon Futures of the Turkish Energy System
(IEEE Computer Society, 2022) Hasturk, I.S.; Kirkil, Gökhan; Celebi, E.; Yucekaya, A.D.; Kirkil, G.
This paper examines the quantitative scenarios for low-carbon futures of the Turkish energy system at aggregated (country level) and regionally disaggregated (NUTS-1 level) levels. We have employed four different storylines for the future European energy system. They are quantified and implemented for the European energy system (30 regions, mostly single countries, including Turkey) using the open-source global energy system model, GENeSYS-MOD v3.0. We have compared the results of all scenarios at aggregated and disaggregated levels and found that there are significant differences among them. Specifically, the hydrogen production (and its use) has increased considerably in the disaggregated model when compared to the aggregated level results. The major reason for these differences is found to be the better estimation of regional renewable capacity factors (wind and solar) in the disaggregated level compared to aggregated level. © 2022 IEEE.