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Autori: Kang Daekook

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Naslov A systematic clinical healthcare model for assessing post-pandemic recovery in heart diagnosis (Article)
Autori Pragathi Subramaniam Narayanamoorthy Samayan Dhivya Selvaraj Saraswathy Ranganathan Simic Vladimir D  Pamucar Dragan S  Kang Daekook 
Info APPLIED SOFT COMPUTING, (2025), vol. 168 br. , str. -
Projekat National Research Foundation (NRF) of Korea - Korean Government (MSIT) [NRF-2024S1A5A8028933]
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Naslov An Adaptive Decision-Making System for Behavior Analysis Among Young Adults (Article)
Autori Pragathi Subramaniam Narayanamoorthy Samayan Pamucar Dragan S  Kang Daekook 
Info COGNITIVE COMPUTATION, (2025), vol. 17 br. 1, str. -
Projekat National Research Foundation (NRF) of Korea - Korean Government (MSIT) [NRF-2022R1C1C1006671]
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Naslov A Trace to Median Index Based Fuzzy Decision Making Technique for Weed Management in Agricultural Systems (Article)
Autori Sandra Michael Narayanamoorthy Samayan Suvitha Krishnan Pamucar Dragan S  Simic Vladimir D  Kang Daekook 
Info IEEE ACCESS, (2024), vol. 12 br. , str. 165185-165202
Projekat Ministry of Education of the Republic of Korea; National Research Foundation of Korea (NRF) [NRF-2024S1A5A8028933]
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Naslov Fuzzy Multi-Criteria Decision Support System for the Best Anti-Aging Treatment Selection Process through Normal Wiggly Hesitant Fuzzy Sets (Article)
Autori Kang Daekook Lakshmanaraj Ramya Narayanamoorthy Samayan Devi Navaneethakrishnan Suganthi Keerthana Kalaiselvan Samayan Saraswathy Ranganathan Pamucar Dragan S  Simic Vladimir D  
Info CMC-COMPUTERS MATERIALS & CONTINUA, (2024), vol. 80 br. 3, str. 4947-4972
Projekat Korean Government (MSIT) [NRF-2022R1C1C1006671]
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Naslov Decision-analytics-based PET plastic recycling selection - a hesitant fuzzy comprehensive ratio assessment model (Article; Early Access)
Autori Suvitha Krishnan Murugesan Veeramuthu Jaisankar Ramasamy Sandra Michael Narayanamoorthy Samayan Pamucar Dragan S  Kang Daekook 
Info ENVIRONMENT DEVELOPMENT AND SUSTAINABILITY, (2024), vol. br. , str. -
Projekat National Research Foundation (NRF) of Korea - Korean Government (MSIT) [NRF-2022R1C1C1006671]
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Naslov An insightful multicriteria model for the selection of drilling technique for heat extraction from geothermal reservoirs using a fuzzy-rough approach (Article)
Autori Sandra Michael Narayanamoorthy Samayan Suvitha Krishnan Pamucar Dragan S  Simic Vladimir D  Kang Daekook 
Info INFORMATION SCIENCES, (2024), vol. 686 br. , str. -
Projekat Ministry of Education of the Republic of Korea; National Research Foundation of Korea (NRF) [NRF-2024S1A5A8028933]
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Naslov A complex fuzzy decision model for analysing the post-pandemic immuno-sustainability (Article)
Autori Pragathi Subramaniam Narayanamoorthy Samayan Dhivya Selvaraj Saraswathy Ranganathan Pamucar Dragan S  Simic Vladimir D  Kang Daekook 
Info ACTA TROPICA, (2024), vol. 256 br. , str. -
Projekat National Research Foundation (NRF) of Korea - Korean Government (MSIT) [NRF- 2022R1C1C1006671]
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Naslov Evaluation of extracting biomass energy using a strategic decision support system (Article)
Autori Suvitha Krishnan Narayanamoorthy Samayan Sandra Michael Pamucar Dragan S  Simic Vladimir D  Kang Daekook 
Info APPLIED SOFT COMPUTING, (2024), vol. 161 br. , str. -
Projekat National Research Foundation (NRF) of Korea - Korean Government (MSIT) [NRF-2022R1C1C1006671]
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Naslov An enhanced decision making model for industrial robotic selection using three factors: Positive, abstained, and negative grades of membership (Article)
Autori Kang Daekook Sandra Michael Narayanamoorthy Samayan Suvitha Krishnan Pamucar Dragan S  Simic Vladimir D  
Info APPLIED SOFT COMPUTING, (2024), vol. 155 br. , str. -
Projekat National Research Foundation (NRF) of Korea - Korean Government (MSIT) [NRF-2022R1C1C1006671]
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Naslov An ideal plastic waste management system based on an enhanced MCDM technique (Article)
Autori Suvitha Krishnan Narayanamoorthy Samayan Pamucar Dragan S  Kang Daekook 
Info ARTIFICIAL INTELLIGENCE REVIEW, (2024), vol. 57 br. 4, str. -
Projekat National Research Foundation (NRF) of Korea grant funded by the Korean Government (MSIT) [NRF-2022R1C1C1006671]; National Research Foundation (NRF) of Korea - Korean Government (MSIT)
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