Mathematical Modeling and Soft Computing in Epidemiology

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1st. "This book describes the use of different mathematical modeling and soft computing techniques used in epidemiology for experiential research in projects such as how infectious diseases progress to show the likely outcome of an epidemic, and to contribute to public health interventions"-- 1. Evolutionary Modelling of Dengue Fever with Incubation Period of Virus 2. Fuzzy-Genetic Approach to Epidemiology 3. Role of Mathematical Models in Physiology and Pathology 4. Machine-Learned Regression Assessment of the HIV Epidemiological Development in Asian Region 5. Mathematical Modeling to Find the Potential Number of Ways to Distribute Certain Things to Certain Places in Medical Field 6. Fractional SIRI Model with Delay in Context of the Generalized Liouville-Caputo Fractional Derivative 7. Optimal Control of a Nipah Virus Transmission Model 8. Application of Eternal Domination in Epidemiology 9. Numerical Analysis of Coupled Time-Fractional Differential Equations Arising in Epidemiological Models 10. Balancing of Nitrogen Mass Cycle for Healthy Living Using Mathematical Model 11. Neutralizing of Nitrogen when the Changes of Nitrogen Content Is Rapid 12. Application of Blockchain Technology in Hospital Information System 13. Complexity Analysis of Pathogenesis of Coronavirus Epidemiology Spread in the China Region 14. A Mathematical Fractional Model to Study the Hepatitis B Virus Infection 15. Nonlinear Dynamics of SARS-CoV2 Virus: India and Its Government Policy 16. Ethical and Professional Issues in Epidemiology 17. Cloud Virtual Image Security for Medical Data Processing 18. Medical Data Security Using Blockchain and Machine Learning Techniques in Cloud Computing 19. Mathematical Model to Avoid Delay Wound Healing by Infinite Element Method 20. Data Classification Framework for Medical Data through Machine Learning Techniques in Cloud Computing Index




Mathematical Modeling and Soft Computing in Epidemiology. (2020). Mathematical Modeling and Soft Computing in Epidemiology. CRC Press.

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