This comprehensive book systematically introduces Dynamic Data Driven Simulation (DDDS) as a new simulation paradigm that makes real-time data and simulation model work together to enable simulation-based prediction/analysis.
The text is significantly dedicated to introducing data assimilation as an enabling technique for DDDS. While data assimilation has been studied in other science fields (e.g., meteorology, oceanography), it is a new topic for the modeling and simulation community.
This unique reference text bridges the two study areas of data assimilation and modelling and simulation, which have been developed largely independently from each other.
Contents:
- Introduction
- Foundation:
- Dynamic System, Simulation, and Data
- Simulation Models and Algorithms
- Basic Probability Concepts
- Dynamic Data-Driven Simulation:
- Dynamic Data Driven Simulation
- Data Assimilation
- Dynamic Data-Driven Simulation for Discrete Simulations
- Application and Look Ahead:
- The Wildfire Spread Simulation Application
- Look Ahead
Readership: Researchers, professionals, academics and graduate students in AI, mathematical modeling and industrial engineering.
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