Mathematical Modeling and Intelligent Control for Combating Pandemics
The contributions in this carefully curated volume, present cutting-edge research in applied mathematical modeling for combating COVID-19 and other potential pandemics. Mathematical modeling and intelligent control have emerged as powerful computational models and have shown significant success in c...
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| Tác giả của công ty: | |
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| Tác giả khác: | , , |
| Định dạng: | Điện tử eBook |
| Ngôn ngữ: | Tiếng Anh |
| Được phát hành: |
Cham :
Springer Nature Switzerland : Imprint: Springer,
2023.
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| Phiên bản: | 1st ed. 2023. |
| Loạt: | Springer Optimization and Its Applications,
203 |
| Những chủ đề: | |
| Truy cập trực tuyến: | https://doi.org/10.1007/978-3-031-33183-1 |
| Các nhãn: |
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Mục lục:
- 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.