Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics

1st Edition - February 11, 2023
Editors: Florentin Smarandache, Muhammad Aslam
Language: English
Paperback ISBN:
9 7 8 - 0 - 3 2 3 - 9 9 4 5 6 - 9
eBook ISBN:
9 7 8 - 0 - 3 2 3 - 9 9 4 5 7 - 6

Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics investigates and presents the many applications that have arisen in the last ten years using neutrosop… Read more

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Cognitive Intelligence with Neutrosophic Statistics in Bioinformatics investigates and presents the many applications that have arisen in the last ten years using neutrosophic statistics in bioinformatics, medicine, agriculture and cognitive science. This book will be very useful to the scientific community, appealing to audiences interested in fuzzy, vague concepts from which uncertain data are collected, including academic researchers, practicing engineers and graduate students. Neutrosophic statistics is a generalization of classical statistics. In classical statistics, the data is known, formed by crisp numbers. In comparison, data in neutrosophic statistics has some indeterminacy. This data may be ambiguous, vague, imprecise, incomplete, and even unknown.

Neutrosophic statistics refers to a set of data, such that the data or a part of it are indeterminate in some degree, and to methods used to analyze the data.

Cover image
Title page
Table of Contents
Copyright
List of contributors
About the editors
Chapter 1. Introduction and advances to neutrosophic probability and statistics and plithogenic probability and statistics and their applications in bioinformatics and other fields (review chapter)
Abstract
1.1 Introduction
1.2 Definitions
1.3 Neutrosophic probability
1.4 Neutrosophic statistics
1.5 Applications of neutrosophic statistics in the medical field and other areas
1.6 Conclusions
References
Chapter 2. Neutrosophic Weibull model with applications to survival studies
Abstract
2.1 Introduction
2.2 Proposed model with some associated functions
2.3 Theoretical background
2.4 Estimation method
2.5 Simulation study
2.6 Illustrative example
2.7 Conclusions
References
Chapter 3. Using the four-valued Rasch model in the preparation of neutrosophic form of risk maps for the spread of COVID-19 in Turkey
Abstract
3.1 Introduction and motivation
3.2 Background, definitions, and notations
3.3 Literature review and state of the art
3.4 Problem/system/application definition
3.5 Proposed solution
3.6 Analysis
3.7 Use cases
3.8 Applications
3.9 Discussion
3.10 Conclusions
3.11 Outlook and future work
References
Chapter 4. Neutrosophic linear models for bioinformatics
Abstract
4.1 Introduction and motivation
4.2 Background, definitions, and notations
4.3 Application of proposed neutrosophic linear models
4.4 Discussion
4.5 Conclusions
References
Chapter 5. Modeling epidemics based on quantum decision-making model by the qutrit states and employing neutrosophic form of percolation analysis
Abstract
5.1 Introduction and motivation
5.2 Background, definitions, and notations
5.3 Literature review and state of the art
5.4 Problem/system/application definition
5.5 Proposed solution
5.6 Analysis
5.7 Use cases
5.8 Applications
5.9 Discussion
5.10 Conclusions
5.11 Outlook and future work
References
Chapter 6. Use of neutrosophic statistics to analyze the measured data of diabetes
Abstract
6.1 Introduction and motivation
6.2 Background, definitions, and abbreviations
6.3 Literature review and state of the art
6.4 Problem
6.5 The proposed solution of the problem
6.6 Analysis of data
6.7 Statistical conditions
6.8 Discussion
6.9 Conclusion
References
Chapter 7. Analysis of changes in blood pressure of women during pregnancy through neutrosophic statistics
Abstract
7.1 Introduction and motivation
7.2 Background, definitions, and abbreviations
7.3 Literature review and state of the art
7.4 Problem
7.5 Proposed solution to the problem
7.6 Analysis of data
7.7 Statistical conditions
7.8 Discussion
7.9 Conclusion
References
Chapter 8. Neutrosophic statistical analysis of changes in blood pressure, pulse rate and temperature of human body due to COVID-19
Abstract
8.1 Introduction and motivation
8.2 Background, definitions, and abbreviations
8.3 Literature review and state of the art
8.4 Problem
8.5 Proposed solution to the problem
8.6 Analysis of data
8.7 Statistical conditions
8.8 Discussion
8.9 Conclusions
References
Chapter 9. A study of human respiration rate through neutrosophic statistics
Abstract
9.1 Introduction and motivation
9.2 Background, definitions, and abbreviations
9.3 Literature review and state of the art
9.4 Problem
9.5 The proposed solution of the problem
9.6 Analysis of data
9.7 Statistical conditions
9.8 Discussion
9.9 Conclusion
References
Chapter 10. Neutrosophic diagnosis of rural women vulnerable to anemia
Abstract
10.1 Introduction and motivation
10.2 Background, definitions, and notations
10.3 Literature review and state of the art
10.4 Problem definition
10.5 Analysis
10.6 Discussion
10.7 Conclusion
References
Chapter 11. Various sampling inspection plans for cancer patients using gamma distribution under indeterminacy
Abstract
11.1 Introduction
11.2 Gamma distribution for indeterminacy
11.3 Single sampling plan under indeterminacy
11.4 Repetitive sampling plan under indeterminacy
11.5 Conclusions
References
Chapter 12. Improved correlation coefficients in neutrosophic statistics for COVID patients using pentapartitioned neutrosophic sets
Abstract
12.1 Introduction
12.2 Preliminaries
12.3 Improved correlation coefficients
12.4 Decision-making using the improved correlation coefficient of pentapartitioned neutrosophic sets
12.5 Interval-valued pentapartitioned neutrosophic sets
12.6 Decision-making using the improved correlation coefficient of IVPNSs
12.7 Decision-making under pentapartitioned neutrosophic environment
12.8 Conclusion
Funding
Acknowledgments
Conflicts of interest
References
Chapter 13. Post-pandemic impact on the occupational shift of rural populace—a case study using neutrosophic comparison t-test
Abstract
13.1 Introduction and motivation
13.2 Literature review and state of the art
13.3 Problem definition
13.4 Conclusion and future work
References
Chapter 14. A novel approach of neutrosophic continuous probability distributions using AH-isometry with applications in medicine
Abstract
14.1 Introduction
14.2 Background, definitions, and notations
14.3 Literature review and state of the art
14.4 Neutrosophic random variables
14.5 Some neutrosophic probability density functions
14.6 Applications and numerical examples
14.7 Discussion
14.8 Conclusions
14.9 Outlook and future work
References
Chapter 15. Monitoring COVID-19 cases under uncertainty
Abstract
15.1 Introduction
15.2 Materials and methods
15.3 Design of neutrosophic control chart
15.4 Results
15.5 Discussions
15.6 Conclusions
References
Chapter 16. Neutrosophic statistical analysis of hybrid work model of medical professionals
Abstract
16.1 Introduction and motivation
16.2 Background, definitions, and notations
16.3 Literature review and state of the art
16.4 Application to the work productivity of medical professionals using hybrid work model
16.5 Discussions
16.6 Conclusion and future work
References
Chapter 17. Neutrosophic regression cum ratio estimators for the population mean: an application in medical science
Abstract
17.1 Introduction
17.2 Proposed neutrosophic estimators
17.3 Empirical study
17.4 Results and discussion
17.5 Conclusion
Acknowledgments
References
Chapter 18. Effectiveness on impact of COVID vaccines on correlation coefficients of pentapartitioned neutrosophic pythagorean statistics
Abstract
18.1 Introduction and motivation
18.2 Background, definitions, and notations
18.3 Correlation measure of pentapartitioned neutrosophic pythagorean sets
18.4 Interval-valued pentapartitioned neutrosophic Pythagorean set
18.5 Application
18.6 Conclusion
References
Chapter 19. Neutrosophic statistics and the medical data: a systematic review
Abstract
19.1 Neutrosophic statistics
References
Chapter 20. Comparative behavior of systolic blood pressure under indeterminacy
Abstract
20.1 Introduction
20.2 Background and motivation
20.3 Methodology
20.4 Sources of data
20.5 Data description
20.6 Interpretation and discussion
20.7 Conclusion
Appendix
References
Chapter 21. Effects of wild medicinal edible plant to prevent COVID-19: a survey by neutrosophic statistics in tribal people of Kokrajhar, Assam, India
Abstract
21.1 Introduction and motivation
21.2 Novelty of the work
21.3 A classification of the wild edible medicinal plant of Kokrajhar
21.4 Data set preparation
21.5 About VIKOR strategy
21.6 Case study
21.7 Result and discussion
21.8 Conclusion
Acknowledgments
References
Chapter 22. Generalized robust-type neutrosophic ratio estimators of pharmaceutical daily stock prices
Abstract
22.1 Introduction
22.2 Terminology
22.3 Some related neutrosophic estimators
22.4 Generalized robust-type neutrosophic ratio estimator
22.5 Simulation study
22.6 Discussion
22.7 Conclusion
References
Chapter 23. Multi-attribute decision-making problem in medical diagnosis using neutrosophic probabilistic distance measures
Abstract
23.1 Introduction
23.2 Preliminaries
23.3 Probabilistic distance measure on single-valued neutrosophic sets
23.4 Methodologies in neutrosophic multi-attribute decision-making problems
23.5 Numerical example: application of single-valued neutrosophic probabilistic distance measures in medical diagnosis
23.6 Results and discussion
23.7 Advantages and limitations
23.8 Conclusions and future work
References
Index

Florentin Smarandache

Prof. Dr. Florentin Smarandache is a professor of mathematics at the University of New Mexico, United states. He is the founder of neutrosophy (generalization of dialectics), neutrosophic set, neutrosophic logic, neutrosophic probability and neutrosophic statistics since 1995 and has published hundreds of papers and books on multispace and multistructure, hypersoft set, degree of dependence and independence between neutrosophic components, refined neutrosophic set, neutrosophic over-under-off-set, plithogenic set, neutrosophic triplet and duplet structures, quadruple neutrosophic structures, extension of algebraic structures to NeutroAlgebras and AntiAlgebras, Dezert Smarandache Theory and so on to many peer-reviewed international journals and many books and he presented papers and plenary lectures to many international conferences around the world.

Affiliations and expertise

Professor, Mathematics and Science Division, University of New Mexico, Gallup, USA

Muhammad Aslam

Muhammad Aslam is a full professor of statistics in the Department of Statistics, King Abdulaziz University, Jeddah, in Saudi Arabia. He has published over 500 research papers in national and international well-reputed journals such as IEEE Access, Journal of Applied Statistics, European Journal of Operation Research, Information Sciences, International Journal of Fuzzy Systems, International Journal of Advanced Manufacturer Technology, and has authored three books published by VDM, Germany, Springer, and Wiley. Professor Aslam is recipient of the Meritorious Service Award in research from NCBAE, as well as the Research Productivity Award from the Pakistan Council for Science and Technology and King Abdulaziz University Excellence Awards in scientific research. He introduced the concept of Neutrosophic Statistical Quality Control (NSQC). He is the founder of Neutrosophic Inferential Statistics (NIS) and NSQC. His areas of interest include industrial statistics, neutrosophic inferential statistics, neutrosophic statistics, neutrosophic quality control, neutrosophic applied statistics, and classical applied statistics.

Affiliations and expertise

Professor, Department of Statistics, King Abdulaziz University, Jeddah, Saudi Arabia

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