Häftad, Engelska, 2025
AI Versus Epidemics
Av James Hughes, Sheridan Houghten, Michael Dubé, Daniel Ashlock, Joseph Alexander Brown, Wendy Ashlock, Matthew Stoodley
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Beskrivning
This book presents algorithms and tools that are designed to model and extract information from personal contact networks, which represent which individuals in a population are physically in contact with one another. The authors developed these tools based on research they conducted during the COVID-19 pandemic, with the goal of improving responses to epidemics in the future. The book provides methods for modelling the transmission of infection across a population. The authors explain how an epidemic model can be used to strategically distribute vaccines and minimize the spread of a virus. The book shows how evolutionary computation, graph compression, and network induction can be utilized to manage issues that arise from an epidemic.
Produktinformation
- Utgivningsdatum: 2025-09-25
- Mått: 168 x 240 x 7 mm
- Vikt: 226 g
- Format: Häftad
- Språk: Engelska
- Antal sidor: 97
- Förlag: Springer International Publishing AG
- Serie: Synthesis Lectures on Learning, Networks, and Algorithms
- ISBN: 9783031643750
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