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.