Browsing by Author "Kang, Daekook"

Now showing 1 - 6 of 6

Citation Count: 1
Assessing performance and satisfaction of micro-mobility in smart cities for sustainable clean energy transportation using novel APPRESAL method
(Elsevier Sci Ltd, 2024) Manirathinam, Thangaraj; Narayanamoorthy, Samayan; Geetha, Selvaraj; Ahmadian, Ali; Ferrara, Massimiliano; Kang, Daekook
South 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.
Citation Count: 1
A bipolar intuitionistic fuzzy decision-making model for selection of effective diagnosis method of tuberculosis
(Elsevier, 2024) Natarajan, Ezhilarasan; Salahshour, Soheıl; Saraswathy, Ranganathan; Narayanamoorthy, Samayan; Salahshour, Soheil; Ahmadian, Ali; Kang, Daekook
Objectives: Tuberculosis (TB) is a contagious illness caused by Mycobacterium tuberculosis. The initial symptoms of TB are similar to other respiratory illnesses, posing diagnostic challenges. Therefore, the primary goal of this study is to design a novel decision-support system under a bipolar intuitionistic fuzzy environment to examine an effective TB diagnosing method. Methods: To achieve the aim, a novel fuzzy decision support system is derived by integrating PROMETHEE and ARAS techniques. This technique evaluates TB diagnostic methods under the bipolar intuitionistic fuzzy context. Moreover, the defuzzification algorithm is proposed to convert the bipolar intuitionistic fuzzy score into crisp score. Results: The proposed method found that the sputum test (T3) is the most accurate in diagnosing TB. Additionally, comparative and sensitivity analyses are derived to show the proposed method's efficiency. Conclusion: The proposed bipolar intuitionistic fuzzy sets, combined with the PROMETHEE-ARAS techniques, proved to be a valuable tool for assessing effective TB diagnosing methods.
Citation Count: 0
Centroid and Graded Mean Ranking Methods for Intuitionistic Trapezoidal Dense Fuzzy Set to Solve MCDM Problems of Robot Selection
(Springer Heidelberg, 2024) Sampathkumar, Swethaa; Augustin, Felix; Narayanamoorthy, Samayan; Ahmadian, Ali; Ferrara, Massimiliano; Kang, Daekook
Fuzzy ranking plays a vital role in decision-making problems and various fuzzy applications. There are plenty of ranking methods that are used to rank fuzzy numbers. However, they fail to give satisfactory results in certain situations due to the complexity of the problem. In this present study, an attempt has been made to introduce four types of ranking methods in the field of intuitionistic dense fuzzy (IDF) depending on centroid and graded mean ranking. Also, arithmetic operations based on lambda 1,lambda 2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\lambda _1, \lambda _2$$\end{document}-cuts, fuzzy numbers, and extension principles are defined for IDF environment. A model is framed to rank MCDM problems, which are aggregated using a weighted aggregation operator and ordered using the proposed and extended ranking methods. To illustrate the proposed MCDM model under the field of IDF, the problem of robot selection is taken for war fighter robots and exoskeleton robots to help and replace humans in war and help assistive walking patients with spinal cord injuries. The result reveals that the Ripsaw and Rewalk emerge as preferable options for substituting humans in the contexts of war fighters and exoskeleton robots, respectively. To analyze the effectiveness of the ranking results, comparative and sensitivity analyses are examined. Thus, the results provide a satisfactory output.
Citation Count: 0
An end-to-end categorizing strategy for green energy sources: Picture q-rung orthopair fuzzy EXPROM-II: MADA approach
(Elsevier, 2024) Parthasarathy, Thirumalai Nallasivan; Narayanamoorthy, Samayan; Sulaiman, Riza; Elamir, Amir Mohamed; Ahmadian, Ali; Kang, Daekook
In today's world, people's need for sustainable energy is crucial. In India, people utilizing 73% of electricity from fossil fuels is the biggest hazard to the environment. In order to partly gratify the nation, policymakers have decided to invest in sustainability renewable energy sources rather than non-renewable resources for the production of energy. There five distinct kinds of green energy sources. The research key contribution is selecting the best renewable energy sources among the five different categories. Therefore, here we form a mathematical fuzzy model to identify the decision received from hesitating knowledge in the form of an Picture Q -rung orthopair fuzzy set (PQROFS) is engaged to handle the uncertain data in decision makers' thoughts. A gathering of relevant judgment Multi -Attribute Decision Analysis (MADA) is employed. Attributes play a prominent role in DM for ranking the alternatives. Here we have twelve attributes and five alternatives. An objective CRiteria Importance Through Intercriteria Correlation (CRITIC) method is employed for attributes priority determination and EXtension of the PROMethee-II (EXPROM-II) method an method is determining the alternative from the preference between each alternative and novel methodology. Ultimately, to validate the proposed results, compared the proposed results with other existing MCDA method results.
Citation Count: 2
A novel decision support system for the appraisal and selection of green warehouses
(Elsevier Science inc, 2024) Sandra, Michael; Narayanamoorthy, Samayan; Ferrara, Massimiliano; Innab, Nisreen; Ahmadian, Ali; Kang, Daekook
Global warming is a prevalent issue across the world. In supply chains, warehouses contribute significantly to the increase in greenhouse gas emissions. Achieving carbon reduction within the warehouse is an issue that must be addressed in the design of a green warehouse. The objective of this research is to establish a hybrid fuzzy multi -criteria decision -making (F-MCDM) paradigm for assisting stakeholders within a supply chain to select a sustainable and green warehouse. A case study is presented to determine the essential criteria for choosing a prospective green warehouse for storing dairy products. Based on the decision-maker's opinion, a total of six criteria are taken from the literature. Besides the criterion "cost", all the other five criteria focused on reducing the environmental footprint. "Bio polyurethane flooring", "polyvinylidene fluoride walls" and "electric forklift" ranked the top three green warehouse selection criteria. The sensitivity study also confirms this analysis and the system's stability. Additionally, the comparative analysis with the existing MCDM models justifies the superiority, reliability, and feasibility of the proposed technique. Moreover, out of the four green warehouse alternatives, warehouse number two got the highest rank. This research thus proves that sustainable building materials and energy -efficient technologies can successfully reduce the environmental footprint caused by warehouses.
Citation Count: 0
A sophisticated decision paradigm for the assessment of hydrogen storage technologies for mobility applications
(Elsevier, 2024) Brainy, Joseph Raj Vikilal Joice; Salahshour, Soheıl; Pragathi, Subramaniam; Salahshour, Soheil; Ahmadian, Ali; Kang, Daekook
In the pursuit of sustainable transportation, hydrogen emerges as a promising zero-emission alternative, offering greater efficiency compared to conventional fuels. However, achieving widespread adoption of hydrogen transportation necessitates a focus on developing efficient onboard storage systems. Therefore, the evaluation of various storage methods becomes pivotal in determining a viable solution for vehicle use, constituting a multi-attribute decision-making challenge. This study aims to create a structured decisionmaking model employing bipolar linear diophantine fuzzy logic, specifically applied to assess hydrogen storage technologies. Bipolar linear diophantine fuzzy sets are introduced to address the inherent uncertainty in decision-making. The framework evaluates the feasibility of four storage systems across ten sustainability criteria. An enhanced LOPCOW-OPA model based on bipolar linear diophantine fuzzy logic is proposed to assess the significance of criteria, while the bipolar linear diophantine fuzzy-based MACONT-MARCOS-ELECTRE-III approach ranks storage technologies. The findings indicate compressed hydrogen storage as an optimal onboard solution for mobile applications. Sensitivity analysis is conducted to gauge how attribute weights and other variables influence the decision-making process. Furthermore, validation of the results obtained through the proposed method is performed via comparative analysis. Moreover, the results obtained can offer valuable insights for the development of hydrogen storage solutions aimed at sustainable and efficient transportation.