Epidemic Analytics for Decision Supports in COVID19 Crisis

Epidemic Analytics for Decision Supports in COVID19 Crisis

Fong, Simon James; Marques, Joao Alexandre Lobo

Springer Nature Switzerland AG

05/2022

158

Dura

Inglês

9783030952808

15 a 20 dias

418

Descrição não disponível.
Chapter 1. Research and Technology Development Achievements During the COVID-19 Pandemic - An Overview.- Chapter 2. Analysis of the COVID-19 Pandemic Behavior based on the Compartmental SEAIRD and Adaptive SVEAIRD Epidemiologic Models.- Chapter 3. The Comparison of Different Linear and Nonlinear Models Using Preliminary Data to Efficiently Analyze the COVID-19 Outbreak.- Chapter 4. Probabilistic Forecasting Model for the COVID-19 Pandemic based on the Composite Monte Carlo Model Integrated with Deep Learning and Fuzzy System.- Chapter 5. The Application of Supervised and Unsupervised Computational Predictive Models to Simulate the COVID-19 Pandemic.- Chapter 6. A Quantum Field formulation for a pandemic propagation.
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Analytics Models;Decision Support;COVID19 Crisis;Epidemiologic Models;Compartmental Simulation Models;Monte-Carlo Simulation Models;Outbreak Analytics;Epidemiological Analysis;Epidemic Analytics;Coronavirus