Mathematical Modeling and Intelligent Control for Combating Pandemics

Part. 1. Mathematical Modeling and analysis for Covid-19 Pandemic.- Chapter. 1. An Extended Fractional SEIR Model to Predict the Spreading Behavior of COVID-19 Disease using Monte-Carlo Back Sampling.- Chapter. 2. Dynamics and optimal control methods for the COVID-19 model.- Chapter. 3. Optimal Strategies to Prevent COVID-19 from Becoming a Pandemic.- Chapter. 4. Modeling and analysis of COVID-19 based on a deterministic compartmental model and Bayesian inference.- Chapter. 5. Predicting the Infection Level of Covid-19 Virus using Normal Distribution Based Approximation Model and PSO.- Chapter. 6. An Optimal Vaccination Scenario for COVID-19 Transmission Between Children and Adults.- Part. 2. Intelligent Control Techniques and Covid-19 Pandemic.- Chapter. 7. The Role of Artificial Intelligence and Machine Learning for the Fight Against COVID-19.- Chapter. 8. Coronavirus Lung Image Classification with Uncertainty Estimation using Bayesian Convolutional Neural Networks.- Chapter.9. Identify Unfavorable COVID Medicine Reactions From The Three-Dimensional Structure By Employing Convolutional Neural Network.- Chapter. 10. Using Reinforcement Learning for optimizing COVID-19 vaccine distribution strategies.- Chapter. 11. Incorporating Contextual Information and Feature Fuzzification for Effective Personalized Healthcare Recommender System.- Chapter. 12. Prediction of Growth and Review of Factors influencing the Transmission of COVID-19.- Chapter. 13. COVID-19 Combating Strategies and Associated Variables for its Transmission: An approach with multi-criteria decision-making techniques in the Indian context.- Chapter. 14. Crisis management, Internet and AI: Information in the age of COVID-19, and future pandemics.