DYNAMIC DATA-DRIVEN SIMULATION: Real-Time Data for Dynamic System Analysis and Prediction

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.

1142196354
DYNAMIC DATA-DRIVEN SIMULATION: Real-Time Data for Dynamic System Analysis and Prediction

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.

86.0 In Stock
DYNAMIC DATA-DRIVEN SIMULATION: Real-Time Data for Dynamic System Analysis and Prediction

DYNAMIC DATA-DRIVEN SIMULATION: Real-Time Data for Dynamic System Analysis and Prediction

by Xiaolin Hu
DYNAMIC DATA-DRIVEN SIMULATION: Real-Time Data for Dynamic System Analysis and Prediction

DYNAMIC DATA-DRIVEN SIMULATION: Real-Time Data for Dynamic System Analysis and Prediction

by Xiaolin Hu

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Overview

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.


Product Details

ISBN-13: 9789811267192
Publisher: WSPC
Publication date: 03/21/2023
Sold by: Barnes & Noble
Format: eBook
Pages: 328
File size: 18 MB
Note: This product may take a few minutes to download.
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