Yazar "Simic, Vladimir" seçeneğine göre listele

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    An integrated bipolar picture fuzzy decision driven system to scrutinize foodwaste treatment technology through assorted factor analysis
    (2024) Devi, Navaneethakrishnan Suganthi Keerthana; Narayanamoorthy, Samayan; Parthasarathy, Thirumalai Nallasivan; Thilagasree, Chakkarapani Sumathi; Pamucar, Dragan; Simic, Vladimir; Dinçer, Hasan; Yüksel, Serhat
    Food Waste (FW) is a pressing environmental concern that affects every country globally. About one-third of the food that is produced ends up as waste, contributing to the carbon footprint. Hence, the FW must be properly treated to reduce environmental pollution. This study evaluates a few available Food Waste Treatment (FWT) technologies, such as anaerobic digestion, composting, landfill, and incineration, which are widely used. A Bipolar Picture Fuzzy Set (BPFS) is proposed to deal with the ambiguity and uncertainty that arise when converting a realworld problem to a mathematical model. A novel Criteria Importance Through Intercriteria Correlation-Stable Preference Ordering Towards Ideal Solution (CRITIC-SPOTIS) approach is developed to objectively analyze FWT selection based on thirteen criteria covering the industry's technical, environmental, and entrepreneurial aspects. The CRITIC method is used for the objective analysis of the importance of each criterion in FWT selection. The SPOTIS method is adopted to rank the alternative hassle-free, following the criteria. The proposed model offers a rank reversal-freemodel, i.e., the rank of the alternatives remains unaffected even after the addition or removal of an alternative. In addition, comparative and sensitivity analyses are performed to ensure the reliability and robustness of the proposed model and to validate the proposed result.
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    Analyzing blockchain-based waste management investments in smart cities using quantum picture fuzzy rough modelling
    (2025) Kou, Gang; Dinçer, Hasan; Pamucar, Dragan; Yüksel, Serhat; Simic, Vladimir
    Blockchain-based waste management investments are key to increase the performance for achieving sustainable growth for both businesses and the country's economy. In this context, a new study should be conducted to identify the most important variables. Accordingly, the purpose of this study is to examine blockchain-based waste management investments via a novel model. The scope of this study is the smart cities that are defined as settlements that aim to improve the quality of life and ensure sustainability by using technology to manage and improve services. Firstly, artificial intelligence (AI) methodology is taken into consideration to compute the weights of the experts. Secondly, the weights of the criteria for blockchain-based waste management investments are computed. Finally, selected investment alternatives for smart cities are ranked with Vise Kriterijumska Optimizacija I Kompromisno Resenje (VIKOR) methodology. Additionally, a comparative analysis is also performed by technique for order preference by similarity (TOPSIS). In addition to this issue, a sensitivity analysis is also conducted with four different cases to check the coherency of the analysis results. The main contribution of this study is the calculation of the expert weights by AI. It is identified that participating in waste to energy schemes has the greatest significance. Similarly, optimizing the lifecycle management has also high weight. It is also defined that integration of physical and digital infrastructures is the most critical alternative. Moreover, urban innovativeness is another critical factor for this situation.