25 research outputs found
Assessing performance and satisfaction of micro-mobility in smart cities for sustainable clean energy transportation using novel APPRESAL method
No full textNarayanamoorthy, Samayan/0000-0002-3782-4666; Ferrara, Massimiliano/0000-0002-3663-836XSouth Korea signed the Global Methane Pledge to reduce methane emissions by 30% by 2030, updated its Nationally Determined Contribution (NDC) to target a 40% reduction in GHGs (Green House Gas) from 2018 levels by 2030. In addition, South Korea submitted its Long -Term Strategy (LTS) to achieve carbon neutrality by 2050. Nowadays, to mitigate the GHG emission every country explicitly planning to reduce non-renewable energy resource vehicles. The electric vehicle (EV) markets growing rapidly with various technologies, strategies and innovations to support decarbonization. In 2022, by the transportation CO2 (Carbon dioxide) emission report of International Energy Agency (IEA), the cars and vans contributes 48% in the over all CO2 emissions. Increasing the electric micro -mobility service would be one of the best effective approach in accordance to reduce CO2 emission. This research study support to reduce the GHG emission by increasing the clean energy vehicle. A case study conducted to analyze firm -wise e -scooter sharing service performance and its satisfaction in smart cities of South Korea. Lacking in the consistent good quality and performance affects the number of electric vehicle users. Hence, electric vehicle firm should focus into their product better performance and quality. This research supports to analyze the e -scooter based on the various criteria from the user's perspective. This research study helps to firms to identify their lacking criteria and improve their quality and performance. We considered the performance, accessibility, tangibility, reliability and responsiveness factors which affects user's perspective in e -scooter sharing services. A survey was conducted over sixty user's for different e -scooter services with twenty four factors. Generally, MCDM (Multi -Criteria Decision -Making) techniques holds two phases to determine the weight of the criteria and another phase to ranking the alternatives. The existing MCDM techniques lacks to handle the user' satisfaction index analysis and not considering the influence grade of each factors in the analysis. To overcome this draw back and analyze the micro -mobility services based over the user's point of view, we introduced a novel fuzzy based MCDM method name as Approach for Preference, Performance and Ranking Evaluation with SAtisfaction Level (APPRESAL) approach. The findings show that Lime, a micro -mobility firm, outperformed other firms with high -quality service and user satisfaction, followed by Wind, XingXing, Alpaca, and Beam. The influences of defected factors from the accessibility, reliability, responsiveness, and assurance dimensions had an adverse effect on quality of firm's micro -mobility service with unsatisfactory performance.National Research Foundation (NRF) of Korea - Korean Government (MSIT) [NRF-2022R1C1C1006671]This work was supported by a National Research Foundation (NRF) of Korea grant funded by the Korean Government (MSIT) Grant NRF-2022R1C1C1006671
Analysis of Vaccine efficacy during the COVID-19 pandemic period using CSF-ELECTRE-I approach
No full textCOVID-19 vaccinations have been shown to be safe, efficacious, and life-saving. They, like other vaccines, do not entirely protect everyone who receives them, and no one knows how effectively they can prevent people from spreading the virus to others or whether the booster dosage is dangerous to some vulnerable people. So, in addition to getting vaccinated, we must continue with additional efforts to combat the pandemic. Quantitatively, the pragmatic, appropriate, and phenomenal mechanism of the complex spherical fuzzy set enhances the decision-making efficacy and the ordering quality of the ELECTRE I method to include a profitable and optimal approach for MAGDM. In the CSF environment, critically ill patients are investigated systematically using a pairwise comparison based ELECTRE-I technique. In this paper, we improve the precision of the CSF-based ELECTRE-I approach to an unique score function. The suggested approach’s comparability is examined with techniques that should provide equal importance to the alternatives, and the presented score function’s reliability is validated using the existing score function with the two cases
Hybrid Hesitant Fuzzy Multi-Criteria Decision Making Method: A Symmetric Analysis of the Selection of the Best Water Distribution System
No full textEvery country’s influence and livelihood is centered on that country’s water source. Therefore, many studies are being conducted worldwide to improve and sustain water resources. In this research paper, we have selected and researched the water scheme for groundwater recharge and drinking water supply of drought prone areas. The water project is aimed at connecting the drought prone areas of the three districts of Tamil Nadu to filling up the ponds in their respective villages and raising the ground water level and meeting the drinking water requirement. We have chosen a multi-criteria decision method to select the best alternative in a complex situation. When reviewing the implementation of this water project, many experts and people who will benefit from this project may have some hesitation and ambiguity in their suggestion on choosing the best water distribution system.We believe that the benefits of this project can be fully availed of if we choose a water distribution system. Our contribution in this article is to choose the best water distribution system for this project by use of our proposed multi-criteria decision making (MCDM) methods, hesitant fuzzy standard deviation with multi-objective optimization method by ratio analysis (HFSDV-MOORA), hesitant fuzzy standard deviation with technique, for order preference by similarity to an ideal solution (HFSDV-TOPSIS) and hesitant fuzzy standard deviation with VIsekriterijumsko Kompromisno Rangiranje (HFSDV-VIKOR), which will provide the best solution for improving the water resource for the drought-prone areas of three districts. Finally, we have identified and compared the correlation coefficient between proposed methods. As a result of the study, it has been found that the best water supply system is closed concrete pipes laid along agricultural land through the rural areas
Selection of suitable biomass conservation process techniques: a versatile approach to normal wiggly interval-valued hesitant fuzzy set using multi-criteria decision making
No full textAbstract A country that relies on developing industrialization and GDP requires a lot of energy. Biomass is emerging as one of the possible renewable energy resources that may be used to generate energy. Through the proper channels, such as chemical, biochemical, and thermochemical processes, it can be turned into electricity. In the context of India, the potential sources of biomass can be broken down into agricultural waste, tanning waste, sewage, vegetable waste, food, meat waste, and liquor waste. Each form of biomass energy so extracted has advantages and downsides, so determining which one is best is crucial to reaping the most benefits. The selection of biomass conversion methods is especially significant since it requires a careful study of multiple factors, which can be aided by fuzzy multi-criteria decision-making (MCDM) models. This paper proposes the normal wiggly interval-valued hesitant fuzzy-based decision-making trial and evaluation laboratory model (DEMATEL) and the Preference Ranking Organization METHod for Enrichment of Evaluations II (PROMETHEE) for assessing the problem of determining a workable biomass production technique. The proposed framework is used to assess the production processes under consideration based on parameters such as fuel cost, technical cost, environmental safety, and C O 2 emission levels. Bioethanol has been developed as a viable industrial option due to its low carbon footprint and environmental viability. Furthermore, the superiority of the suggested model is demonstrated by comparing the results to other current methodologies. According to comparative study, the suggested framework might be developed to handle complex scenarios with many variables
Extended hesitant fuzzy SWARA techniques to examine the criteria weights and VIKOR method for ranking alternatives
No full textCOMPREHENSIVE DISTANCE-BASED RANKING METHOD FOR EVALUATING HYDRAULIC CONVERTERS IN TIDAL STREAM TURBINES UTILIZING PICTURE FERMATEAN FUZZY SET
No full textIn recent years, advancements in hydrokinetic technology and the growing demand for renewable energy have heightened interest in water-based energy extraction. This study proposes a new fuzzy information representation technique, Probabilistic Picture Fermatean Fuzzy Sets (PPFFSs), to investigate the selection of hydrokinetic energy harnessing technologies (HEHT) for various marine and river-based applications. To address the complexity of multiple criteria and alternatives, we developed a new integrated multi-criteria decision-making (MCDM) model that incorporates logarithmic percentage change-driven objective weighting (LOPCOW) and comprehensive distance-based ranking (COBRA) approaches. We define PPFFS as the definition of basic functions and the provision of information scoring and accurate operational processes. According to the results, the efficiency factor is the most important criterion, and the Seagen tidal stream turbine outperforms all other tidal turbines. The findings are supported by experimental data from the HEHT and a comparison of how two hydrokinetic energy converters can improve efficiency. As a result, hydrokinetic systems are one of the greatest sustainable energy solutions for distant communities and small-scale applications
Intuitionistic fuzzy MAUT-BW Delphi method for medication service robot selection during COVID-19
No full textCoronavirus 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
A dual hesitant q-rung orthopair enhanced MARCOS methodology under uncertainty to determine a used PPE kit disposal
No full textHealthcare waste management is regarded as the most critical concern that the entire world is currently and will be confronted with in the near future. During the COVID-19 pandemic, the significant growth in medical waste frightened the globe, prompting it to investigate safe disposal methods. Plastics are developing as a severe environmental issue as a result of their increased use during the COVID-19 pandemic which has triggered a global catastrophe and prompted concerns about plastic waste management. One of the biggest challenges in this circumstance is the disposal of discarded PPE kits. The purpose of this research is to find a viable disposal treatment procedure for enhanced personal protective equipment (PPE) (facemasks, gloves, and other protective equipment) and other single-use plastic medical equipment waste in India during the COVID-19 crises, which will aid in effectively reducing their increasing quantity. To analyse the PPE waste disposal problem in India, we used the fuzzy Measurement Alternatives and Ranking according to the Compromise Solution (MARCOS) technique, which included the dual hesitant q-rung orthopair fuzzy set. The fuzzy Best Worst Method (BWM), which is compatible with the existing MCDM approaches, is used to establish the criteria weights. Sensitivity and comparative analyses are utilised to confirm the stability and validity of the proposed strategy
A Distinctive Symmetric Analyzation of Improving Air Quality Using Multi-Criteria Decision Making Method under Uncertainty Conditions
No full textThis world has a wide range of technologies and possibilities that are available to control air pollution. Still, finding the best solution to control the contamination of the air without having any impact on humans is a complicated task. This proposal helps to improve the air quality using the multi-criteria decision making method. The decision to improve air quality is a challenging problem with today’s technology and environmental development level. The multi-criteria decision making method is quite often faced with conditions of uncertainty, which can be tackled by employing fuzzy set theory. In this paper, based on an objective weighting method (CCSD), we explore the improved fuzzy MULTIMOORA approach. We use the classical Interval-Valued Triangular Fuzzy Numbers (IVTFNs), viz. the symmetric lower and upper triangular numbers, as the basis. The triangular fuzzy number is identified by the triplets; the lowest, the most promising, and the highest possible values, symmetric with respect to the most promising value. When the lower and upper membership functions are equated to one, we get the normalized interval-valued triangular fuzzy numbers, which consist of symmetric intervals. We evaluate five alternatives among the four criteria using an improved MULTIMOORA method and select the best method for improving air quality in Tamil Nadu, India. Finally, a numerical example is illustrated to show the efficiency of the proposed method
OPTIMIZING NON-INVASIVE REMOTE SENSING FOR GEOTHERMAL EXPLORATION WITH T-SPHERICAL DUAL HESITANT FUZZY DECISION MODEL
No full textTraditional geothermal detection methods, such as extensive ground-based surveys and drillings, are often costly, time-consuming, and environmentally intrusive. To address these challenges, this study presents a novel hybrid fuzzy multi-criteria decision-making model to evaluate and prioritize non-invasive, cost-effective remote sensing (RS) techniques. This model uses T-spherical dual-hesitant fuzzy set to manage the inherent ambiguities in the evaluation of multiple criteria. The logarithmic percentage change-driven objective weighting technique assigns the relative importance of criteria, and the multiple triangle scenarios-II methodology helps in comprehensive evaluation and ranking. By incorporating expert judgment and addressing inherent uncertainties, this model provides a systematic framework for optimizing RS technique selection. Findings indicate that thermal infrared imaging, with a significance score of 0.7187, holds transformative potential for geothermal energy development. Sensitivity and comparative analyses further confirm the robustness of this approach. This research offers a valuable resource for energy developers and policymakers aiming to leverage RS technologies for efficient geothermal resource management and development
