Forecasting sustainable development level of selected Asian countries using M-EDAS and k-NN algorithm
Yıl 2023,
, 101 - 112, 30.06.2023
Çiğdem Özarı
,
Esin Nesrin Can
,
Agah Alıcı
Öz
This study aims to forecast the sustainable development levels of countries with the least possible parameters based on social, economic, and environmental dimensions. For this purpose, a hybrid model consisting of multi-criteria decision-making and machine learning methods is proposed. First, using the M-EDAS method, selected Asian countries were ranked based on the main goals of the Sustainable Development Report. By using ranking findings, sustainability development levels were determined for 2017–2020. Using the last two years before the relevant year as a training dataset, the sustainable development levels determined for 2019-2020 were estimated using two basic macroeconomic variables. 2020 forecast findings are not successful as 2019. Additionally, the findings obtained from the ranking analysis were evaluated using Spearman's correlation to compare the periods before and during the COVID-19 pandemic.
Teşekkür
Some part of this study was previously published as Congress abstract paper. (Oriental Business and Innovation Center Conference, 5-6 May 2022, Budapest).
Kaynakça
- Abdel-Basset, M., & Mohamed, R. (2020). A Novel Plithogenic TOPSIS-Critic Model for Sustainable Supply Chain Risk Management. Journal of Cleaner Production. 247, 1-15. https://doi.org/10.1016/j.jclepro.2019.119586
- Aggarwal, A., Choudhary, C., & Mehrotra, D. (2018). Evaluation Of Smartphones In Indian Market Using EDAS. Procedia Computer Science. 132, 236-243. https://doi.org/10.1016/j.procs.2018.05.193
- 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.
- Almulhim, T. S. (2019). Multi-Criteria Evaluation of Insurance Industries Performance: An Analysis of EDAS Based On The Entropy Weight. International Journal for Quality Research, 14(4), 1097-1114. https://doi.org/10.24874/IJQR14.04-07
- Ayan, T. Y., Ünal, H., & Samut, S. (2017). A Comparative Analysis of European And Central Asian Countries From The Economic Dimension Of Sustainable Development: Cluster Analysis And TOPSIS Method. Route Educational and Social Science Journal. 4(6), 202-213.
- Baral, S., Shekar, K. R., Sharma, M.& Rao, P. V. (2014). Optimization of Leaching Parameters for The Extraction of Rare Earth Metal Using Decision Making Method. Hydrometallurgy. 143, 60-67. https://doi.org/10.1016/j.hydromet.2014.01.006
- Behzad, M., Zolfani, S. H., Pamucar, D., & Behzad, M. (2020). A Comparative Assessment of Solid Waste Management Performance In The Nordic Countries Based On BWM-EDAS. Journal of Cleaner Production. 266, 1-11. https://doi.org/10.1016/j.jclepro.2020.122008
- Bhuvaneswari, P., & Therese, A. B. (2015). Detection Of Cancer in Lung With K-NN Classification Using Genetic Algorithm. Procedia Materials Science, 10, 433-440.
- Candan, G., & Cengiz Toklu, M. (2022). Sustainable Industrialization Performance Evaluation of European Union Countries: An Integrated Spherical Fuzzy Analytic Hierarchy Process And Grey Relational Analysis Approach. International Journal of Sustainable Development & World Ecology, 29(5), 1-14. https://doi.org/10.1080/13504509.2022.2027293
- Cherif, W. (2018). Optimization of K-NN Algorithm by Clustering And Reliability Coefficients: Application To Breast-Cancer Diagnosis. Procedia Computer Science, 127, 293-299.
- Choudhary, D., Singh, A. K., & Tiwari, S. (2013). A Statistical Approach for Iris Recognition Using K-NN Classifier. International Journal of Image, Graphics and Signal Processing, 5(4), 46-52. https://doi.org/10.5815/ijigsp.2013.04.06
- Colglazier, W. (2015). Sustainable Development Agenda: 2030. Science, 349(6252), 1048-1050.
- Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining Objective Weights in Multiple Criteria Problems: The Critic Method. Computers & Operations Research, 22(7), 763-770.
- Ecer, F. (2018). Third-party Logistics (3PLs) Provider Selection Via Fuzzy AHP and EDAS Integrated Model. Technological and Economic Development of Economy, 24(2), 615-634. https://doi.org/10.3846/20294913.2016.1213207
- Ehsani, R., & Drabløs, F. (2020). Robust Distance Measures For k-NN Classification of Cancer Data. Cancer informatics, 19, https://doi.org/10.1177/117693512096554
- Ela, M., & Soysal Kurt, H. (2019). Comparison of Macroeconomic Performances of Sub-Saharan African Countries with TOPSIS Method. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 10(3), 547-555.
- Feng, X., Wei, C. & Liu, Q. (2018). EDAS Method for Extended Hesitant Fuzzy Linguistic Multi-criteria Decision Making. International Journal of Fuzzy Systems. 20, 2470–2483. https://doi.org/10.1007/s40815-018-0504-5
- Gorbenkova, E., Shcherbina, E., & Belal, A. (2018). Rural Areas: Critical Drivers For Sustainable Development. IFAC-PapersOnLine, 51(30), 786-790. https://doi.org/10.1016/j.ifacol.2018.11.195
- Ghalehno, R. K. (2021). Modification Of the EDAS Method For Controlling Outlier Data. Journal of Industrial Engineering International, 17(3), 91-108.
- Hák, T., Janoušková, S., & Moldan, B. (2016). Sustainable Development Goals: A Need For Relevant Indicators. Ecological Indicators, 60(1), 565-573. https://doi.org/10.1016/j.ecolind.2015.08.003
- Hassanat, A. B. (2014). Dimensionality Invariant Similarity Measure. Journal of American Science,10(8), 221-226.
- Huda, S., & Chowanda, A. (2021). Personality Prediction from Text On Social Media With Machine Learning. ICIC Express Letters, 15(12),1243-1251.
- Ilieva, G., Yankova, T., & Klisarova-Belcheva, S. (2018). Decision Analysis with Classic And Fuzzy EDAS Modifications. Computational and Applied Mathematics, 37(5), 5650-5680.
- Kahraman, C., Keshavarz Ghorabaee, M., Bhuvaneswari, E. K., Cevik Onar, S., Yazdani, M., & Oztaysi, B. (2017). Intuitionistic Fuzzy Edas Method: An Application to Solid Waste Disposal Site Selection. Journal of Environmental Engineering and Landscape Management, 25(1), 1-12. https://doi.org/10.3846/16486897.2017.1281139
- Keshavarz-Ghorabaee, M. (2021). A simple modification to the EDAS method for two exceptional cases. BOHR International Journal of Advances in Management Research, 1(1), 36-39. https://www.preprints.org/manuscript/202104.0111/v1
- Keshavarz-Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS Method For Fuzzy Multi-Criteria Decision-Making: An Application to Supplier Selection. International Journal of Computers Communications & Control, 11(3), 358-371.
- Keshavarz-Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria Inventory Classification Using a New Method of Evaluation Based On Distance From Average Solution (EDAS). Informatica, 26(3), 435-451. http://dx.doi.org/10.15388/Informatica.2015.57
- Krishnan, A. R., Kasim, M. M., Hamid, R., & Ghazali, M. F. (2021). A Modified CRITIC Method to Estimate the Objective Weights Of Decision Criteria. Symmetry, 13(6), 973. https://doi.org/10.3390/sym13060973
- Lotfi, F. H., & Fallahnejad, R. (2010). Imprecise Shannon’s Entropy and Multi Attribute Decision Making. Entropy, 12(1), 53-62. https://doi.org/10.3390/e12010053
- Mehta, S., Shen, X., Gou, J., & Niu, D. (2018). A New Nearest Centroid Neighbor Classifier Based on K Local Means Using Harmonic Mean Distance. Information, 9(9), 1-16.
- Mukid, M. A., Widiharih, T., Rusgiyono, A., & Prahutama, A. (2018). Credit Scoring Analysis Using Weighted K Nearest Neighbor. Journal of Physics: Conference Series, 1025, 1-7. https://doi.org/10.1088/1742-6596/1025/1/012114.
- Mutlu M., & Sarı, M. (2017). Çok Kriterli Karar Verme Yöntemleri ve Madencilik Sektöründe Kullanımı. Bilimsel Madencilik Dergisi, 56(4),181-196.
- Ondrus, J., Bui, T., & Pigneur, Y. (2015). A Foresight Support System Using MCDM Methods. Group Decision and Negotiation, 24(2), 333-358.
- Ozari, Ç, Can, E. N., & Alıcı A. (2022). Predicting the Sustainable Development Level of Selected Asian Countries Using the Modified EDAS Method and K-NN Algorithm, Oriental Business and Innovation Center Conference, Challenges and Sustainability In The Post-Covid-19 Era: Asian Responses To Economic, Security, And Social Dilemmas Book Of Abstracts.
- Pacheco, W. D. N., & López, F. R. J. (2019). Tomato Classification According to Organoleptic Maturity (Coloration) Using Machine Learning Algorithms K-NN, MLP, and K-Means Clustering. XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA)1-5.
- Paradowski, B., Shekhovtsov, A., Bączkiewicz, A., Kizielewicz, B., & Sałabun, W. (2021). Similarity Analysis of Methods for Objective Determination of Weights In Multi-Criteria Decision Support Systems. Symmetry, 13(10), 1-23. https://doi.org/10.3390/sym13101874
- Pereira, J., Contreras, P., Morais, D. C., & Arroyo-López, P. (2022). A Multi-Criteria and Stochastic Robustness Analysis Approach To Compare Nations Sustainability. Socio-Economic Planning Sciences, 80, 1-14. https://doi.org/10.1016/j.seps.2021.101159
- Ramteke, R., & Monali, K. (2012). Automatic Medical Image Classification and Abnormality Detection Using K-Nearest Neighbour. International Journal of Advanced Computer Research, 2(4), Issue:6, 190-196.
- Ren, J., Hu, C. H., Yu, S. Q., & Cheng, P. F. (2021). An Extended EDAS Method Under Four-Branch Fuzzy Environments and Its Application in Credit Evaluation for Micro And Small Entrepreneurs. Soft Computing, 25(4), 2777-2792.
- Shannon, C. E., & Weaver, W. (1947). The Math Theory of Communica. Urbana: The University of Illinois Press.
- Shaw, S., Josi, K., Pathak, A., Thyagarajan, A. K., Vidya, G., Shah, R. H., Kishan, V. R., & Alex. J. S. R. (2021). Anomaly Detection in Drones with Machine Learning Algorithms. Futuristic Communication and Network Technologies, 792, 433-441. https://doi.org/ 10.1007/978-981-16-4625-6_42.
- Skvarciany, V., Jurevičienė, D., & Volskytė, G. (2020). Assessment Of Sustainable Socio-Economic Development in European Union Countries. Sustainability, 12(5), 2-19. https://doi.org/10.3390/su12051986.
- Skvarciany, V., Lapinskaitė, I., & Volskytė, G. (2021). Circular Economy as Assistance For Sustainable Development In OECD Countries. Oeconomia Copernicana, 12(1), 11-34. https://doi.org/10.24136/oc.2020.001
- Singh, M., & Pant, M. (2021). A Review of Selected Weighing Methods in MCDM With A Case Study. International Journal of System Assurance Engineering and Management, 12(1), 126-144. https://doi.org/10.1007/s13198-020-01033-3
- Stanujkic, D., Popovic, G., Zavadskas, E. K., Karabasevic, D., & Binkyte-Veliene, A. (2020). Assessment of progress towards achieving Sustainable Development Goals of the “Agenda 2030” by using the CoCoSo and the Shannon Entropy methods: The case of the EU Countries. Sustainability, 12(14), 5717. https://doi.org/10.3390/su12145717
- Sun, F., & Yu, J. (2021). Improved Energy Performance Evaluating and Ranking Approach For Office Buildings Using Simple-normalization, Entropy-based TOPSIS and K-means Method. Energy Reports, 7, 1560-1570. https://doi.org/10.1016/j.egyr.2021.03.007
- Tharwat, A., Mahdi, H., Elhoseny, M., & Hassanien, A. E. (2018). Recognizing Human Activity in Mobile Crowdsensing Environment Using Optimized k-NN Algorithm. Expert Systems with Applications, 107, 32-44. https://doi.org/10.1016/j.eswa.2018.04.017
- Torkayesh, A. E., & Torkayesh, S. E. (2021). Evaluation Of Information and Communication Technology Development In G7 Countries: An Integrated MCDM Approach. Technology In Society, 66, 1-9. https://doi.org/10.1016/j.techsoc.2021.101670
- Yazdani, M., Torkayesh, A. E., Santibanez-Gonzalez, E. D., & Otaghsara, S. K. (2020). Evaluation Of Renewable Energy Resources Using Integrated Shannon Entropy—EDAS Model. Sustainable Operations and Computers, 1, 35-42. https://doi.org/10.1016/j.susoc.2020.12.002
- Wang, T.C., & Lee, H.D. (2009). Developing A Fuzzy TOPSIS Approach Based on Subjective Weights and Objective Weights. Expert Systems Applications, 36(5), 8980–8985. https://doi.org/10.1016/j.eswa.2008.11.035
- Xing, W., & Yilin B. (2017). Medical Health Big Data Classification Based on KNN Classification Algorithm. Preparation of Papers for IEEE Access,1-12, 28808-28819.
- Zavadskas, E. K., Stević, Ž., Turskis, Z., & Tomašević, M. (2019). A Novel Extended EDAS In Minkowski Space (EDAS-M) Method for Evaluating Autonomous Vehicles. Studies in Informatics and Control, 28(3), 255-264.
Yıl 2023,
, 101 - 112, 30.06.2023
Çiğdem Özarı
,
Esin Nesrin Can
,
Agah Alıcı
Kaynakça
- Abdel-Basset, M., & Mohamed, R. (2020). A Novel Plithogenic TOPSIS-Critic Model for Sustainable Supply Chain Risk Management. Journal of Cleaner Production. 247, 1-15. https://doi.org/10.1016/j.jclepro.2019.119586
- Aggarwal, A., Choudhary, C., & Mehrotra, D. (2018). Evaluation Of Smartphones In Indian Market Using EDAS. Procedia Computer Science. 132, 236-243. https://doi.org/10.1016/j.procs.2018.05.193
- 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.
- Almulhim, T. S. (2019). Multi-Criteria Evaluation of Insurance Industries Performance: An Analysis of EDAS Based On The Entropy Weight. International Journal for Quality Research, 14(4), 1097-1114. https://doi.org/10.24874/IJQR14.04-07
- Ayan, T. Y., Ünal, H., & Samut, S. (2017). A Comparative Analysis of European And Central Asian Countries From The Economic Dimension Of Sustainable Development: Cluster Analysis And TOPSIS Method. Route Educational and Social Science Journal. 4(6), 202-213.
- Baral, S., Shekar, K. R., Sharma, M.& Rao, P. V. (2014). Optimization of Leaching Parameters for The Extraction of Rare Earth Metal Using Decision Making Method. Hydrometallurgy. 143, 60-67. https://doi.org/10.1016/j.hydromet.2014.01.006
- Behzad, M., Zolfani, S. H., Pamucar, D., & Behzad, M. (2020). A Comparative Assessment of Solid Waste Management Performance In The Nordic Countries Based On BWM-EDAS. Journal of Cleaner Production. 266, 1-11. https://doi.org/10.1016/j.jclepro.2020.122008
- Bhuvaneswari, P., & Therese, A. B. (2015). Detection Of Cancer in Lung With K-NN Classification Using Genetic Algorithm. Procedia Materials Science, 10, 433-440.
- Candan, G., & Cengiz Toklu, M. (2022). Sustainable Industrialization Performance Evaluation of European Union Countries: An Integrated Spherical Fuzzy Analytic Hierarchy Process And Grey Relational Analysis Approach. International Journal of Sustainable Development & World Ecology, 29(5), 1-14. https://doi.org/10.1080/13504509.2022.2027293
- Cherif, W. (2018). Optimization of K-NN Algorithm by Clustering And Reliability Coefficients: Application To Breast-Cancer Diagnosis. Procedia Computer Science, 127, 293-299.
- Choudhary, D., Singh, A. K., & Tiwari, S. (2013). A Statistical Approach for Iris Recognition Using K-NN Classifier. International Journal of Image, Graphics and Signal Processing, 5(4), 46-52. https://doi.org/10.5815/ijigsp.2013.04.06
- Colglazier, W. (2015). Sustainable Development Agenda: 2030. Science, 349(6252), 1048-1050.
- Diakoulaki, D., Mavrotas, G., & Papayannakis, L. (1995). Determining Objective Weights in Multiple Criteria Problems: The Critic Method. Computers & Operations Research, 22(7), 763-770.
- Ecer, F. (2018). Third-party Logistics (3PLs) Provider Selection Via Fuzzy AHP and EDAS Integrated Model. Technological and Economic Development of Economy, 24(2), 615-634. https://doi.org/10.3846/20294913.2016.1213207
- Ehsani, R., & Drabløs, F. (2020). Robust Distance Measures For k-NN Classification of Cancer Data. Cancer informatics, 19, https://doi.org/10.1177/117693512096554
- Ela, M., & Soysal Kurt, H. (2019). Comparison of Macroeconomic Performances of Sub-Saharan African Countries with TOPSIS Method. Gümüşhane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 10(3), 547-555.
- Feng, X., Wei, C. & Liu, Q. (2018). EDAS Method for Extended Hesitant Fuzzy Linguistic Multi-criteria Decision Making. International Journal of Fuzzy Systems. 20, 2470–2483. https://doi.org/10.1007/s40815-018-0504-5
- Gorbenkova, E., Shcherbina, E., & Belal, A. (2018). Rural Areas: Critical Drivers For Sustainable Development. IFAC-PapersOnLine, 51(30), 786-790. https://doi.org/10.1016/j.ifacol.2018.11.195
- Ghalehno, R. K. (2021). Modification Of the EDAS Method For Controlling Outlier Data. Journal of Industrial Engineering International, 17(3), 91-108.
- Hák, T., Janoušková, S., & Moldan, B. (2016). Sustainable Development Goals: A Need For Relevant Indicators. Ecological Indicators, 60(1), 565-573. https://doi.org/10.1016/j.ecolind.2015.08.003
- Hassanat, A. B. (2014). Dimensionality Invariant Similarity Measure. Journal of American Science,10(8), 221-226.
- Huda, S., & Chowanda, A. (2021). Personality Prediction from Text On Social Media With Machine Learning. ICIC Express Letters, 15(12),1243-1251.
- Ilieva, G., Yankova, T., & Klisarova-Belcheva, S. (2018). Decision Analysis with Classic And Fuzzy EDAS Modifications. Computational and Applied Mathematics, 37(5), 5650-5680.
- Kahraman, C., Keshavarz Ghorabaee, M., Bhuvaneswari, E. K., Cevik Onar, S., Yazdani, M., & Oztaysi, B. (2017). Intuitionistic Fuzzy Edas Method: An Application to Solid Waste Disposal Site Selection. Journal of Environmental Engineering and Landscape Management, 25(1), 1-12. https://doi.org/10.3846/16486897.2017.1281139
- Keshavarz-Ghorabaee, M. (2021). A simple modification to the EDAS method for two exceptional cases. BOHR International Journal of Advances in Management Research, 1(1), 36-39. https://www.preprints.org/manuscript/202104.0111/v1
- Keshavarz-Ghorabaee, M., Zavadskas, E. K., Amiri, M., & Turskis, Z. (2016). Extended EDAS Method For Fuzzy Multi-Criteria Decision-Making: An Application to Supplier Selection. International Journal of Computers Communications & Control, 11(3), 358-371.
- Keshavarz-Ghorabaee, M., Zavadskas, E. K., Olfat, L., & Turskis, Z. (2015). Multi-criteria Inventory Classification Using a New Method of Evaluation Based On Distance From Average Solution (EDAS). Informatica, 26(3), 435-451. http://dx.doi.org/10.15388/Informatica.2015.57
- Krishnan, A. R., Kasim, M. M., Hamid, R., & Ghazali, M. F. (2021). A Modified CRITIC Method to Estimate the Objective Weights Of Decision Criteria. Symmetry, 13(6), 973. https://doi.org/10.3390/sym13060973
- Lotfi, F. H., & Fallahnejad, R. (2010). Imprecise Shannon’s Entropy and Multi Attribute Decision Making. Entropy, 12(1), 53-62. https://doi.org/10.3390/e12010053
- Mehta, S., Shen, X., Gou, J., & Niu, D. (2018). A New Nearest Centroid Neighbor Classifier Based on K Local Means Using Harmonic Mean Distance. Information, 9(9), 1-16.
- Mukid, M. A., Widiharih, T., Rusgiyono, A., & Prahutama, A. (2018). Credit Scoring Analysis Using Weighted K Nearest Neighbor. Journal of Physics: Conference Series, 1025, 1-7. https://doi.org/10.1088/1742-6596/1025/1/012114.
- Mutlu M., & Sarı, M. (2017). Çok Kriterli Karar Verme Yöntemleri ve Madencilik Sektöründe Kullanımı. Bilimsel Madencilik Dergisi, 56(4),181-196.
- Ondrus, J., Bui, T., & Pigneur, Y. (2015). A Foresight Support System Using MCDM Methods. Group Decision and Negotiation, 24(2), 333-358.
- Ozari, Ç, Can, E. N., & Alıcı A. (2022). Predicting the Sustainable Development Level of Selected Asian Countries Using the Modified EDAS Method and K-NN Algorithm, Oriental Business and Innovation Center Conference, Challenges and Sustainability In The Post-Covid-19 Era: Asian Responses To Economic, Security, And Social Dilemmas Book Of Abstracts.
- Pacheco, W. D. N., & López, F. R. J. (2019). Tomato Classification According to Organoleptic Maturity (Coloration) Using Machine Learning Algorithms K-NN, MLP, and K-Means Clustering. XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA)1-5.
- Paradowski, B., Shekhovtsov, A., Bączkiewicz, A., Kizielewicz, B., & Sałabun, W. (2021). Similarity Analysis of Methods for Objective Determination of Weights In Multi-Criteria Decision Support Systems. Symmetry, 13(10), 1-23. https://doi.org/10.3390/sym13101874
- Pereira, J., Contreras, P., Morais, D. C., & Arroyo-López, P. (2022). A Multi-Criteria and Stochastic Robustness Analysis Approach To Compare Nations Sustainability. Socio-Economic Planning Sciences, 80, 1-14. https://doi.org/10.1016/j.seps.2021.101159
- Ramteke, R., & Monali, K. (2012). Automatic Medical Image Classification and Abnormality Detection Using K-Nearest Neighbour. International Journal of Advanced Computer Research, 2(4), Issue:6, 190-196.
- Ren, J., Hu, C. H., Yu, S. Q., & Cheng, P. F. (2021). An Extended EDAS Method Under Four-Branch Fuzzy Environments and Its Application in Credit Evaluation for Micro And Small Entrepreneurs. Soft Computing, 25(4), 2777-2792.
- Shannon, C. E., & Weaver, W. (1947). The Math Theory of Communica. Urbana: The University of Illinois Press.
- Shaw, S., Josi, K., Pathak, A., Thyagarajan, A. K., Vidya, G., Shah, R. H., Kishan, V. R., & Alex. J. S. R. (2021). Anomaly Detection in Drones with Machine Learning Algorithms. Futuristic Communication and Network Technologies, 792, 433-441. https://doi.org/ 10.1007/978-981-16-4625-6_42.
- Skvarciany, V., Jurevičienė, D., & Volskytė, G. (2020). Assessment Of Sustainable Socio-Economic Development in European Union Countries. Sustainability, 12(5), 2-19. https://doi.org/10.3390/su12051986.
- Skvarciany, V., Lapinskaitė, I., & Volskytė, G. (2021). Circular Economy as Assistance For Sustainable Development In OECD Countries. Oeconomia Copernicana, 12(1), 11-34. https://doi.org/10.24136/oc.2020.001
- Singh, M., & Pant, M. (2021). A Review of Selected Weighing Methods in MCDM With A Case Study. International Journal of System Assurance Engineering and Management, 12(1), 126-144. https://doi.org/10.1007/s13198-020-01033-3
- Stanujkic, D., Popovic, G., Zavadskas, E. K., Karabasevic, D., & Binkyte-Veliene, A. (2020). Assessment of progress towards achieving Sustainable Development Goals of the “Agenda 2030” by using the CoCoSo and the Shannon Entropy methods: The case of the EU Countries. Sustainability, 12(14), 5717. https://doi.org/10.3390/su12145717
- Sun, F., & Yu, J. (2021). Improved Energy Performance Evaluating and Ranking Approach For Office Buildings Using Simple-normalization, Entropy-based TOPSIS and K-means Method. Energy Reports, 7, 1560-1570. https://doi.org/10.1016/j.egyr.2021.03.007
- Tharwat, A., Mahdi, H., Elhoseny, M., & Hassanien, A. E. (2018). Recognizing Human Activity in Mobile Crowdsensing Environment Using Optimized k-NN Algorithm. Expert Systems with Applications, 107, 32-44. https://doi.org/10.1016/j.eswa.2018.04.017
- Torkayesh, A. E., & Torkayesh, S. E. (2021). Evaluation Of Information and Communication Technology Development In G7 Countries: An Integrated MCDM Approach. Technology In Society, 66, 1-9. https://doi.org/10.1016/j.techsoc.2021.101670
- Yazdani, M., Torkayesh, A. E., Santibanez-Gonzalez, E. D., & Otaghsara, S. K. (2020). Evaluation Of Renewable Energy Resources Using Integrated Shannon Entropy—EDAS Model. Sustainable Operations and Computers, 1, 35-42. https://doi.org/10.1016/j.susoc.2020.12.002
- Wang, T.C., & Lee, H.D. (2009). Developing A Fuzzy TOPSIS Approach Based on Subjective Weights and Objective Weights. Expert Systems Applications, 36(5), 8980–8985. https://doi.org/10.1016/j.eswa.2008.11.035
- Xing, W., & Yilin B. (2017). Medical Health Big Data Classification Based on KNN Classification Algorithm. Preparation of Papers for IEEE Access,1-12, 28808-28819.
- Zavadskas, E. K., Stević, Ž., Turskis, Z., & Tomašević, M. (2019). A Novel Extended EDAS In Minkowski Space (EDAS-M) Method for Evaluating Autonomous Vehicles. Studies in Informatics and Control, 28(3), 255-264.