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Title:
Data with Turiyam Set and its Graphical Visualization for Decision Making Processing |
Abstract:
Recently the precise measurement of dark data sets is considered as one of the crucial problems for data processing tasks. To deal with this issue, several mathematical theories as well as geometry are proposed. One of them is the Turiyam set which provides a way to explore the unknown or dark data set based on expert consciousness. In this talk some of the data sets containing Turiyam attributes and its exploration will be discussed for knowledge processing tasks. Same time the non-Euclidean graphical visualization will also be discussed. |
Biography:
Dr. Prem Kumar Singh working as Full Professor at Department of Computer Science and Engineering, Gandhi Institute of Technology and Management-Visakhapatnam, Andhra Pradesh-India 530045. He has more than 14 Years of experience in teaching, research and academics. He holds a Post-Doc in Computer Science from Faculty of Computer Science and Information Technology, University of Malaya-Kuala Lumpur which was fully funded by HIR Lab Malaysian Govt of Higher Education. He has completed a PhD degree in Computer Science from Vellore Institute of Technology-Vellore which was fully funded by NBHM Department of Atomic Energy, Govt of India. He has published more than 110 peer review research papers in several conferences and Journals. All of those researches cited more than 2300, 27 h-indexes and more than 60 i10 papers. His current research interests are soft computing, complex data analysis, graph theory, mathematical modelling and Quantum machine intelligence. Towards this direction, he has introduced bipolar, three-polar, m-polar, complex, Plithogenic and Turiyam graphs for knowledge processing tasks. He served as Technical Program Committee, Reviewer, Guest Editor, Editorial board member as well as Speaker for more than 300 peer reviewed conferences and journals. He is Editor-In-Chief for “Journal of Neutrosophic and Fuzzy Systems” and Associate Editor for “Journal of Artificial Intelligence and Technology”. He is also listed as Top 2% Scientist by Stanford University in 2019, 2020, 2021, 2022 and 2023 as well.
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