Browsing by Author "Akay, Diyar"

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Generating Linguistic Advice for the Carbon Limit Adjustment Mechanism
(SPRINGER, 2024) Fidan, Fatma Şener; Aydoğan, Sena; Akay, Diyar; 0000-0002-2397-3628; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Fidan, Fatma Şener
Linguistic summarization, a subfield of data mining, generates summaries in natural language for comprehending big data. This approach simplifies the incorporation of information into decision-making processes since no specialized knowledge is needed to understand the generated language summaries. The present research employs linguistic summarization to examine the circumstances surrounding the Carbon Border Adjustment Mechanism, one of the most significant regulations confronting exporting nations to the European Union, and will be adopted to support sustainable growth. In this paper, associated with several attributes of the countries and product flow from exporting countries to European countries were defined as nodes and relations, respectively. Before the modeling phase, fuzzy c-means automatically identified fuzzy sets and membership degrees of attributes. During the modeling phase, summary forms were generated using polyadic quantifiers. A total of 1944 linguistic summaries were produced between exporting countries and European countries. Thirty-five summaries have a truth degree greater than or equal to the threshold value of 0.9, which is considered reasonable. The provision of natural language descriptions of the Carbon Border Adjustment Mechanism is intended to aid decision-makers and policymakers in their deliberations.
Investigating the carbon border adjustment mechanism transition process with linguistic summarization method: A situational analysis of exporting countries
(ELSEVIER, 2024) Şener Fidan, Fatma; Aydoğan, Sena; Akay, Diyar; 0000-0002-2397-3628; AGÜ, Mühendislik Fakültesi, Endüstri Mühendisliği Bölümü; Şener Fidan, Fatma
The Paris Agreement holds significant importance since it establishes a global framework for addressing the issue of climate change and endeavors to mitigate the release of greenhouse gases. The Carbon Border Adjustment Mechanism was introduced as an integral component of this agreement, aiming to oversee the carbon emissions associated with imported items within the European Union and provide compensation for the emissions from the nations engaged in importation. It is essential to analyze the countries involved in exporting to the European Union within the Carbon Border Adjustment Mechanism context to mitigate carbon leakage and effectively support the objectives outlined in the Paris Agreement. This research investigated 104 nations engaged in exporting activities to 27 European Union member countries. The linguistic summarization method, a descriptive data analytics tool, was employed for the analysis. A total of 42 Combined Nomenclature codes were encompassed within the scope of evaluation throughout the transition phase of the Carbon Border Adjustment Mechanism. This study examines the characteristics of exporting nations based on three variables: The Environmental Performance Index, a sustainability indicator; the Region in which the countries are located as classified by the World Bank; and the quantity of Renewable Energy Consumption. Additionally, the study explores the characteristics of EU countries, focusing on their Environmental Performance Index score and geography. The study employed fuzzy sets and the fuzzy c-means algorithm as parts of the linguistic summarization technique. Polyadic quantifiers were used to extract linguistic summaries, resulting in the acquisition of 124,227 summaries. A total of 1594 summaries have a truth degree exceeding 0.9. The findings were effectively utilized to assess the influence of the linguistic summarization approach and offered a valuable viewpoint for decision-makers needing more expertise in this domain.