Mathematical Modeling and Intelligent Control for Combating Pandemics / / edited by Zakia Hammouch, Mohamed Lahby, Dumitru Baleanu |
Edizione | [1st ed. 2023.] |
Pubbl/distr/stampa | Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 |
Descrizione fisica | 1 online resource (278 pages) |
Disciplina |
006.3
362.1969015118 |
Collana | Springer Optimization and Its Applications |
Soggetto topico |
System theory
Control theory Mathematics Systems Theory, Control Applications of Mathematics Epidèmies Sistemes de control per retroacció Models matemàtics |
Soggetto genere / forma | Llibres electrònics |
ISBN | 3-031-33183-4 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | 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. |
Record Nr. | UNINA-9910744502103321 |
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2023 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Time series analysis : forecasting and control / / George E.P. Box, Gwilym M. Jenkins, Gregory C. Reinsel |
Autore | Box George E. P |
Edizione | [4th ed.] |
Pubbl/distr/stampa | Hoboken, N.J., : John Wiley, c2008 |
Descrizione fisica | 1 online resource (781 p.) |
Disciplina |
519.5/5
519.55 |
Altri autori (Persone) |
JenkinsGwilym M
ReinselGregory C |
Collana | Wiley series in probability and statistics |
Soggetto topico |
Anàlisi de sèries temporals
Teoria de la predicció Sistemes de control per retroacció Control automàtic Models matemàtics Time-series analysis Prediction theory Transfer functions Feedback control systems - Mathematical models |
Soggetto genere / forma | Llibres electrònics |
ISBN |
9781118619193
1118619196 9781118619063 1118619064 9781118210871 1118210875 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto | pt. 1. Stochastic models and their forecasting -- pt. 2. Stochastic model building -- pt. 3. Transfer function and multivariate model building -- pt. Design of discrete control schemes -- pt. 5. Charts and tables -- pt. 6. Exercises and problems. |
Record Nr. | UNINA-9910141180203321 |
Box George E. P | ||
Hoboken, N.J., : John Wiley, c2008 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|