WoS İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653
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Article Citation - WoS: 62Citation - Scopus: 70The Novel Augmented Fermatean Mcdm Perspectives for Identifying the Optimal Renewable Energy Power Plant Location(Elsevier, 2022) Parthasarathy, Thirumalai Nallasivan; Pragathi, Subramaniam; Shanmugam, Ponnan; Baleanu, Dumitru; Ahmadian, Ali; Kang, Daekook; Narayanamoorthy, SamayanThe Fermatean fuzzy set has been authorized as a suitable tool for the uncertainty and vagueness of information by augmenting the spatial space of acceptance membership and non-acceptance membership degrees of both intuitionistic and Pythagorean fuzzy sets. Solar energy does not emit any hazardous gases into the atmosphere, making it one of the most effective strategies to reduce global warming in the environment. Under a variety of circumstances, finding a spot for a photovoltaic solar power plant might be difficult. As a result, we experiment with multi-criteria decision-making (MCDM) techniques. We presented a hybrid technique based on the PV-SPSS method based on the Removal Effects of Criteria (MEREC) and Multiple Objective Optimization on the Basis of Ratio Analysis with Full Multiplicative Form (MULTIMOORA) analysis. The MEREC approach is used to calculate the weightage of each attribute, and MULTIMOORA is used to find the ranking of the alternatives. Also, a new rectified generalized score function determines the score value of FFSs. Culmination: the validity of the result is assessed by implementing the existing MCDM approaches and by changing the criterion weight.Article Citation - WoS: 24Citation - Scopus: 29Intuitionistic Fuzzy Maut-Bw Delphi Method for Medication Service Robot Selection During Covid-19(Elsevier, 2022) Devi, S. Aicevarya; Felix, Augustin; Narayanamoorthy, Samayan; Kalaiselvan, Samayan; Balaenu, Dumitru; Ahmadian, Ali; Kang, DaekookABS T R A C T Coronavirus Disease 2019 (COVID-19), a new illness caused by a novel coronavirus, a member of the corona family of viruses, is currently posing a threat to all people, and it has become a significant challenge for healthcare organizations. Robotics are used among other strategies, to lower COVID's fatality and spread rates globally. The robot resembles the human body in shape and is a programmable mechanical device. As COVID is a highly contagious disease, the treatment for the critical stage COVID patients is decided to regulate through medication service robots (MSR). The use of service robots diminishes the spread of infection and human error and prevents frontline healthcare workers from exposing themselves to direct contact with the COVID illness. The selection of the most appropriate robot among different alternatives may be complex. So, there is a need for some mathematical tools for proper selection. Therefore, this study design the MAUT-BW Delphi method to analyze the selection of MSR for treating COVID patients using integrated fuzzy MCDM methods, and these alternatives are ranked by influencing criteria. The trapezoidal intuitionistic fuzzy numbers are beneficial and efficient for expressing vague information and are defuzzified using a novel algorithm called converting trapezoidal intuitionistic fuzzy numbers into crisp scores (CTrIFCS). The most suitable criteria are selected through the fuzzy Delphi method (FDM), and the selected criteria are weighted using the simplified best-worst method (SBWM). The performance between the alternatives and criteria is scrutinized under the multi-attribute utility theory (MAUT) method. Moreover, to assess the effectiveness of the proposed method, sensitivity and comparative analyses are conducted with the existing defuzzification techniques and distance measures. This study also adopt the idea of a correlation test to compare the performance of different defuzzification methods.Article Citation - WoS: 21Citation - Scopus: 24A New Extension of Hesitant Fuzzy Set: an Application To an Offshore Wind Turbine Technology Selection Process(inst Engineering Technology-iet, 2021) Ramya, Lakshmanaraj; Kang, Daekook; Baleanu, Dumitru; Kureethara, Joseph Varghese; Annapoorani, Veerappan; Narayanamoorthy, SamayanWind energy is an energy source that is naturally clean, safe and cheap. It comes from a variety of sources. The electric energy generated by a wind turbine manifests as kinetic energy throughout the earth. The energy received from the wind is clean and is permanently available and can be generated forever. Turbine characteristics also have an impact on wind energy production. The turbine properties within a wind farm are important in estimating the load on power generation and wind turbine energy. The amount of energy released is calculated according to the type of the turbine model applied. In many situations, the choices of turbine model can incur various vague and complicated hesitation situations. To manage this situation, a hesitant fuzzy set with the Multi Criteria Decision Making (MCDM) is used. In the present research, the newly proposed Normal Wiggly Hesitant Fuzzy-Criteria Importance Through Intercriteria Correlation (NWHF-CRITIC) and Normal Wiggly Hesitant Fuzzy-Multi Attribute Utility Theory (NWHF-MAUT) methods were employed to rank turbine models based on quality, power level, voltage, and capacity. As part of this process, the NWHF method was utilized to extract and gather deeper information from the decision-makers.