An Intelligent and Robust Framework towards Anomaly Detection, Medical Diagnosis, and Shortest Path Problems Based on Interval-Valued T-Spherical Fuzzy Information
Joint Authors
Jin, Huanhuan
Jah Rizvi, Syed Khurram
Jan, Naeem
Ullah, Kifayat
Saleem, Shahzad
Mahmood, Tahir
Source
Mathematical Problems in Engineering
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-23, 23 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-11-24
Country of Publication
Egypt
No. of Pages
23
Main Subjects
Abstract EN
The recent emerging advancements in the domain of the fuzzy sets are the framework of the T-spherical fuzzy set (TSFS) and interval valued T-spherical fuzzy set (IVTSFS).
Keeping in view the promising significance of the latest research trend in the fuzzy sets and the enabling impact of IVTSFS, we proposed a novel framework for decision assembly using interval valued TSFS based upon encompassing the four impressive dimensions of human judgement including favor, abstinence, disfavor, and refusal degree.
Another remarkable contribution is the optimization of information modeling and prevention of information loss by redefining the concept of each membership in interval.
Moreover, the proposed research made a worthy contribution work by demonstrating the effective utilization of the interval valued TSFS based framework in anomaly detection, medical diagnosis, and shortest path problem.
The proposed work demonstrates the effective remedial measure for the anomaly detection problem based on several parameters using the aggregation operators of IVTSFS.
Moreover, the interval valued T-spherical fuzzy relations and their composition are illustrated to investigate the medical diagnosis problem.
Furthermore, the notion of interval valued T-spherical fuzzy graph is also presented and fundamental notions of graph theory are also demonstrated with the help of real world instances.
In the context of interval valued T-spherical fuzzy graphs (IVTSFGs), a modified Dijkstra Algorithm (DA) is developed and applied to the shortest path problem.
The in-depth quantitative assessment and comparative analysis revealed that the proposed notion outpaces contemporary progressive approaches.
American Psychological Association (APA)
Jin, Huanhuan& Jah Rizvi, Syed Khurram& Mahmood, Tahir& Jan, Naeem& Ullah, Kifayat& Saleem, Shahzad. 2020. An Intelligent and Robust Framework towards Anomaly Detection, Medical Diagnosis, and Shortest Path Problems Based on Interval-Valued T-Spherical Fuzzy Information. Mathematical Problems in Engineering،Vol. 2020, no. 2020, pp.1-23.
https://search.emarefa.net/detail/BIM-1202398
Modern Language Association (MLA)
Jin, Huanhuan…[et al.]. An Intelligent and Robust Framework towards Anomaly Detection, Medical Diagnosis, and Shortest Path Problems Based on Interval-Valued T-Spherical Fuzzy Information. Mathematical Problems in Engineering No. 2020 (2020), pp.1-23.
https://search.emarefa.net/detail/BIM-1202398
American Medical Association (AMA)
Jin, Huanhuan& Jah Rizvi, Syed Khurram& Mahmood, Tahir& Jan, Naeem& Ullah, Kifayat& Saleem, Shahzad. An Intelligent and Robust Framework towards Anomaly Detection, Medical Diagnosis, and Shortest Path Problems Based on Interval-Valued T-Spherical Fuzzy Information. Mathematical Problems in Engineering. 2020. Vol. 2020, no. 2020, pp.1-23.
https://search.emarefa.net/detail/BIM-1202398
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1202398