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ÖgeA distance-based approach to fuzzy cognitive maps using pythagorean fuzzy sets(Springer, 2024)Fuzzy Cognitive Maps (FCMs) have been attracting researchers from a wide application area due to being easy to apply and interpret. Since its proposal, the method has been improved to satisfy the diverse needs of practitioners such as solving different types of problems and representing particular types of uncertainty. The classical FCMs depend highly on the decision-maker judgments and the uncertainty inherent in the judgments deserves significant attention. Although there are several fuzzy extensions integrated into FCMs, the uncertainty caused by the lack of knowledge, the hesitancy of decision makers, and also the limited capacity of humans to deal with pre-defined rules should be considered. To address this issue, a new distance-based approach integrating Pythagorean Fuzzy Sets and FCMs is proposed. To the best of our knowledge, this is the first time this extension is integrated into FCMs. Besides allowing to represent the uncertainty until the end of the calculations, the new approach offers decision makers an easier and more flexible way to assess the strength of existing causal relationships. To provide a comparison between the proposed approach and the classical FCMs, two real-life applications are selected as case studies.
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ÖgeElectric vehicles as an emission mitigation option : expectations and reality(Springer, 2024)Globally, the reliance on thermal power, constituting 67% of electricity generation, prompts questions for many countries regarding the viability of electric vehicles (EVs) for emission reduction in the transportation sector. This study comprehensively analyzes CO2 emissions in the small family car segment, considering engines powered by different energy sources. The analysis is coupled with Worldwide Harmonized Light Vehicle Test Procedure driving profiles, accounting for specific ambient temperature structures representative of densely populated areas in Türkiye. The constructed model incorporates the hourly temperature of the relevant cities and the hourly electricity production mix by considering the indirect emissions and comparing the ICEVs (Internal Combustion Engine Vehicles) and EVs in different time frames from 2015 to 2020. The resulting emissions from each vehicle type in each city and driving profile, along with the ratio of instances in which EVs exhibit higher emissions than ICEVs, are presented.The findings reveal the intricate interplay between vehicle type, climate conditions, and driving profiles. While the urban driving profile emerges as superior for EVs regarding CO2 reduction, offering a comfortable driving experience without range anxiety and mitigating local pollutants, it exhibits less significant carbon emission reductions at lower and higher speed profiles, particularly in cold climate conditions. EVs are not a silver bullet but a valuable technology for emissions reduction under specific conditions. Policymakers are urged to consider factors favoring EVs over ICEVs regarding CO2 emissions, such as driving profiles, time and climatic conditions when formulating investment policies and subsidies.