Evaluating Environmental Sustainability Position of Turkey Via Bric and Mint Countries With K-Nn Algorithm
Abstract
Environmental sustainability is one of the biggest difficulties met by humanity. It is also one pillar of sustainable development purposes required to be executed. For evaluating and comparing all world countries with respect to this perspective, an index is derived from the United Nations. With this index, the countries of the world are divided into four categories, such as “Very High Developed (VHD)”, “High Developed (HD)”, “Medium Developed (MD)” and lastly, “Low Developed (LD)”. According to the 2019 environmental sustainable index value, Turkey is located in the VHD category. Some of the experts put forward that Turkey will compete with economic giants in 2050. Our hope economically continued efforts will be achieved environmentally also. These thoughts became the starting point of this study. With this aim, the position of Turkey is predicted with the BRIC and MINT countries data regarding to environmental sustainability with the k-NN (Nearest Neighbor) algorithm technique.
References
- [1]Ali, Z., Abbas, A. W., Thasleema, T. M., Uddin, B., Raaz, T., & Abid, S. A. R. (2015). Database development and automatic speech recognition of isolated Pashto spoken digits using MFCC and K-NN. International Journal of Speech Technology, 18(2), 271-275. [2]Alkhatib, K., Najadat, H., Hmeidi, I., &Shatnawi, M. K. A. (2013). Stock price prediction using k-nearest neighbor (k-NN) algorithm. International Journal of Business, Humanities and Technology, 3(3), 32-44. [3]Bradshaw, C. J., Giam, X., & Sodhi, N. S. (2010). Evaluating the relative environmental impact of countries. PloS one, 5(5). [4]Cover, T.M., Hart, P.E.(1967), Nearest neighbor pattern classification. IEEE Trans. Inf. Theory IT-13, 21–27 [5]Dadush, U. B.,& Stancil, B. (2010). The world order in 2050. Carnegie Endowment for International Peace. [6]Deng, Z., Zhu, X., Cheng, D., Zong, M., & Zhang, S. (2016). Efficient k-NN classification algorithm for big data. Neurocomputing, 195, 143-148. [7]El Katat, S., Kalakech, A., Kalakech, M., & Hamad, D. (2019). Financial Development Indicators: A Comparative Study between Lebanon and Middle East Countries Based on Data Mining Techniques. Internatıonal Arab Journal Of Informatıon Technology, 16(3 A), 499-505. [8]Ferranti, P., Berry, E., & Jock, A. (2018). Encyclopedia of Food Security and Sustainability. Elsevier. [9]Goodland,R.(1995).Theconceptofenvironmentalsustainability.Annual review of ecology and systematics, 26(1), 1-24. [10]Hawksworth, J.,& Cookson, G. (2006). The world in 2050. How big will the major emerging market economies get and how can the OECD compete. [11]Jiang, S., Pang, G., Wu, M., &Kuang, L. (2012). An improved K-nearest-neighbor algorithm for text categorization. Expert Systems with Applications, 39(1), 1503-1509. [12]Kurniadi, D., Abdurachman, E., Warnars, H. L. H. S., &Suparta, W. (2018, November). The prediction of scholarship recipients in higher education using k-Nearest neighbor algorithm. In IOP Conference Series: Materials Science and Engineering (Vol. 434, No. 1, p. 012039). IOP Publishing. [13]Li, B., Yu, S., & Lu, Q. (2003). An improved k-nearest neighbor algorithm for text categorization. arXiv preprint cs/0306099. [14]Li, F.,& Jin, G. (2019). Research on power energy load forecasting method based on K-NN. International Journal of Ambient Energy, 1-6. [15]O’neill, J. (2001). Building better global economic BRICs.in Global Economics Paper No: 66, GS Global Economics Website, available online at https://www.goldmansachs.com/insights/archive/index.html [16]Scherer, L., Behrens, P., de Koning, A., Heijungs, R., Sprecher, B., &Tukker, A. (2018). Trade-offs between social and environmental Sustainable Development Goals. Environmental Science & Policy, 90, 65-72. [17]Scherer, L., de Koning, A., &Tukker, A. (2019). BRIC and MINT countries’ environmental impacts rising despite alleviative consumption patterns. Science of the Total Environment, 665, 52-60. [18]P. Soucy and G. W. Mineau, “A simple K-NN algorithm for text categorization,” Proceedings 2001 IEEE International Conference on Data Mining, San Jose, CA, USA, 2001, pp. 647-648. [19]Todeschini, R. (1990). Weighted k-nearest neighbour method for the calculation of missing values. Chemometrics and Intelligent Laboratory Systems, 9(2), 201-205. [20]Ward, J. D., Sutton, P. C., Werner, A. D., Costanza, R., Mohr, S. H., & Simmons, C. T. (2016). Is decoupling GDP growth from environmental impact possible?. PloS one, 11(10). [21]Y. Wang and Z. Wang, “A Fast K-NN Algorithm for Text Categorization,” 2007 International Conference on Machine Learning and Cybernetics, Hong Kong, 2007, pp. 3436-3441. [22]Zhang, S., Cheng, D., Deng, Z., Zong, M., & Deng, X. (2018). A novel k-NN algorithm with data-driven k parameter computation. Pattern Recognition Letters, 109, 44-54. URL 1: http://hdr.undp.org/en/content/dashboard-4-environmental- sustainability-0
Türkiye’nin Çevresel Sürdürülebilirlik Kategorisinin Brıc ve Mınt Ülkeleri Yardımıyla K-Nn Algoritması Üzerinden Değerlendirilmesi
Abstract
Çevresel sürdürülebilirlik, insanlığın günümüz dünyasında yüzleştiği en büyük sorunlardan biridir. Ayrıca sürdürülebilir kalkınmanın tüm yönleriyle yürütülmesi açısından oldukça önemli bir parçasıdır. Tüm dünya ülkelerini çevresel sürdürülebilirlik açısından değerlendirmek ve karşılaştırmak için Birleşmiş Milletler bir endeks türetmiştir. Çevresel sürdürülebilirlik indeksi olarak oluşturulan bu indeks ile ülkeler “Çok Yüksek Gelişmiş”, “Gelişmiş”, “Orta Gelişmiş” ve son olarak da “Düşük Gelişmiş” olmak üzere dört farklı kategoride sınıflandırılmaktadır. 2019 çevresel sürdürülebilir endeks değerine göre, Türkiye son sıralarda da olsa Çok Yüksek Gelişme göstermiş ülke kategorisinde yer almaktadır. Türkiye›nin 2050’li yıllarda ise ekonomik devlerle rekabet edeceğini öne sürülmektedir. Umudumuz ekonomik olarak devam eden çabalarımızın çevresel olarak da sağlanması yönündedir. Bu düşünceler bu çalışmanın başlangıç noktası olmuştur. Bu amaçla, Türkiye›nin çevresel sürdürülebilirlik kategorisi, k-NN (k-En Yakın Komşu) algoritma tekniği ile BRIC (Brezilya, Rusya, Hindistan, Çin) ve MINT (Meksika, Endonezya, Nijerya, Türkiye) ülkeleri verileri yardımıyla tahmin edilmiştir.
References
- [1]Ali, Z., Abbas, A. W., Thasleema, T. M., Uddin, B., Raaz, T., & Abid, S. A. R. (2015). Database development and automatic speech recognition of isolated Pashto spoken digits using MFCC and K-NN. International Journal of Speech Technology, 18(2), 271-275. [2]Alkhatib, K., Najadat, H., Hmeidi, I., &Shatnawi, M. K. A. (2013). Stock price prediction using k-nearest neighbor (k-NN) algorithm. International Journal of Business, Humanities and Technology, 3(3), 32-44. [3]Bradshaw, C. J., Giam, X., & Sodhi, N. S. (2010). Evaluating the relative environmental impact of countries. PloS one, 5(5). [4]Cover, T.M., Hart, P.E.(1967), Nearest neighbor pattern classification. IEEE Trans. Inf. Theory IT-13, 21–27 [5]Dadush, U. B.,& Stancil, B. (2010). The world order in 2050. Carnegie Endowment for International Peace. [6]Deng, Z., Zhu, X., Cheng, D., Zong, M., & Zhang, S. (2016). Efficient k-NN classification algorithm for big data. Neurocomputing, 195, 143-148. [7]El Katat, S., Kalakech, A., Kalakech, M., & Hamad, D. (2019). Financial Development Indicators: A Comparative Study between Lebanon and Middle East Countries Based on Data Mining Techniques. Internatıonal Arab Journal Of Informatıon Technology, 16(3 A), 499-505. [8]Ferranti, P., Berry, E., & Jock, A. (2018). Encyclopedia of Food Security and Sustainability. Elsevier. [9]Goodland,R.(1995).Theconceptofenvironmentalsustainability.Annual review of ecology and systematics, 26(1), 1-24. [10]Hawksworth, J.,& Cookson, G. (2006). The world in 2050. How big will the major emerging market economies get and how can the OECD compete. [11]Jiang, S., Pang, G., Wu, M., &Kuang, L. (2012). An improved K-nearest-neighbor algorithm for text categorization. Expert Systems with Applications, 39(1), 1503-1509. [12]Kurniadi, D., Abdurachman, E., Warnars, H. L. H. S., &Suparta, W. (2018, November). The prediction of scholarship recipients in higher education using k-Nearest neighbor algorithm. In IOP Conference Series: Materials Science and Engineering (Vol. 434, No. 1, p. 012039). IOP Publishing. [13]Li, B., Yu, S., & Lu, Q. (2003). An improved k-nearest neighbor algorithm for text categorization. arXiv preprint cs/0306099. [14]Li, F.,& Jin, G. (2019). Research on power energy load forecasting method based on K-NN. International Journal of Ambient Energy, 1-6. [15]O’neill, J. (2001). Building better global economic BRICs.in Global Economics Paper No: 66, GS Global Economics Website, available online at https://www.goldmansachs.com/insights/archive/index.html [16]Scherer, L., Behrens, P., de Koning, A., Heijungs, R., Sprecher, B., &Tukker, A. (2018). Trade-offs between social and environmental Sustainable Development Goals. Environmental Science & Policy, 90, 65-72. [17]Scherer, L., de Koning, A., &Tukker, A. (2019). BRIC and MINT countries’ environmental impacts rising despite alleviative consumption patterns. Science of the Total Environment, 665, 52-60. [18]P. Soucy and G. W. Mineau, “A simple K-NN algorithm for text categorization,” Proceedings 2001 IEEE International Conference on Data Mining, San Jose, CA, USA, 2001, pp. 647-648. [19]Todeschini, R. (1990). Weighted k-nearest neighbour method for the calculation of missing values. Chemometrics and Intelligent Laboratory Systems, 9(2), 201-205. [20]Ward, J. D., Sutton, P. C., Werner, A. D., Costanza, R., Mohr, S. H., & Simmons, C. T. (2016). Is decoupling GDP growth from environmental impact possible?. PloS one, 11(10). [21]Y. Wang and Z. Wang, “A Fast K-NN Algorithm for Text Categorization,” 2007 International Conference on Machine Learning and Cybernetics, Hong Kong, 2007, pp. 3436-3441. [22]Zhang, S., Cheng, D., Deng, Z., Zong, M., & Deng, X. (2018). A novel k-NN algorithm with data-driven k parameter computation. Pattern Recognition Letters, 109, 44-54. URL 1: http://hdr.undp.org/en/content/dashboard-4-environmental- sustainability-0
Details
| Primary Language | English |
|---|---|
| Subjects | Economics |
| Journal Section | Research Article |
| Authors | |
| Publication Date | April 1, 2020 |
| Published in Issue | Year 2020 Volume: 6 Issue: 1 |
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