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The purpose of this study is to identify the key factors to minimize carbon emission problem. Within this framework, an examination has been made by considering both data mining and fuzzy decision-making techniques. In the analysis process, N-gram methodology is implemented to the abstracts of 1711 studies in the "Sciencedirect" platform and five different indicators are selected. In the proposed decision-making model, firstly, selected criteria are weighted by Spherical fuzzy CRITIC. Secondly, E7 economies are ranked with RATGOS. Thirdly, a sensitivity analysis is performed, and a comparative evaluation is conducted by MAIRCA technique. The most important originality of this proposed model is generating a new technique named RATGOS. In the literature, there are various decision-making models to rank the alternatives. However, lots of researchers criticized these approaches due to some reasons, such as using Euclidean distance by calculating the distances to the negative ideal solutions. Thus, it is seen that there is a need for a new technique that considers geometric mean in proportional concepts. To reach this objective, the RATGOS technique is introduced so that it can be possible to reach more accurate results. The findings indicate that renewable energy usage is the most critical item to overcome carbon emission problem. Therefore, some measures should be taken to increase renewable energy investments. First, governments can offer incentives for renewable energy investments. These incentives may include various incentives such as tax exemptions and low interest loans. Moreover, more research and development works are required for the development of renewable energy technologies. In this way, it can make renewable energy technologies more effective and efficient. For future research directions, an evaluation can be carried out for developed countries because carbon emissions problem also plays a crucial role for the social and economic improvements of these economies. [ABSTRACT FROM AUTHOR]

The main performance indicators of hydrogen energy production should be improved. However, improving these factors also increase the operational costs of the companies. Because of this issue, there is a need for a priority analysis so that it can be possible to focus on more important factors. Accordingly, the purpose of this study is to evaluate hydrogen production methods for global energy transition. In this process, a four-stage model has been proposed by getting evaluations from three different experts. Firstly, artificial intelligence-based decision-making can be implemented for expert prioritization. In the second stage, recommender system is conducted with collaborative filtering to complete the missing evaluations. Thirdly, selected criteria are weighted by using M-SWARA with QPFRS. Finally, method alternatives for hydrogen production are ranked via quantum picture fuzzy rough sets adopted VIKOR. The biggest contribution for doing this study is that artificial intelligence technique is integrated into the model and experts' importance coefficients are can be computed. Additionally, by using the collaborative filtering technique, empty evaluations can be filled scientifically. This contributes to the quality of the analysis process in many ways. Thanks to this technique, experts are given the opportunity not to answer questions they are not very sure about. The findings indicate that renewable energy expansion, energy efficiency and sustainable development are the most important criteria for global energy transition in hydrogen production. On the other side, the ranking results give information that thermal processes including steam methane reforming and biomass gasification is the most appropriate method alternatives for hydrogen production. Based on these analysis results, it is strongly recommended that research and development activities should be improved to increase the efficiency and effectiveness of the renewable energy projects. With the help of this issue, it can be much easier to increase the performance of hydrogen production process. • Hydrogen production methods are evaluated for global energy transition. • A four-stage model has been proposed. • Selected criteria are weighted by using M-SWARA. • Method alternatives for hydrogen production are ranked via VIKOR. • Renewable energy expansion is the most important criteria. [ABSTRACT FROM AUTHOR]

Summary: This study aims to evaluate the significant risks in geothermal energy investments. For this purpose, a model is suggested by considering the Spherical fuzzy DEMATEL technique. With the help of the literature examination, eight important risks are identified for these projects. In the following step, their weights are calculated so that more significant risk issues can be understood. Another calculation is also performed by triangular fuzzy DEMATEL to check the consistency of the analysis results. The results of both Spherical and triangular fuzzy DEMATEL techniques are similar. The most essential risk issues are the same for both methods that demonstrate the validity of the findings. The results indicate that the risk of accidents because of incorrect design‐material use has the greatest importance since it has the highest weight. Moreover, the risks of decreased water resources and pollution of them also play a significant role in this regard. Great attention should be paid to the quality of the material to be used in geothermal energy facilities. Otherwise, there is a risk of explosion and fire in the facility. These problems threaten the lives of many people. In this process, states also have very important duties. Some standards should be determined for the quality of the material used in these facilities. In addition, the compliance of the quality of these materials with the regulations should be checked with the routine inspections. This situation will minimize the risk of accidents due to using poor‐quality materials. [ABSTRACT FROM AUTHOR]