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A Hardware-in-Loop Digital Twin Approach for Intelligent Optimization of Municipal Solid Waste Incineration
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A Hardware-in-Loop Digital Twin Approach for Intelligent Optimization of Municipal Solid Waste Incineration : AI and Its Application to Complex Industries

Book Details

Format Hardback or Cased Book
ISBN-10 1394354010
ISBN-13 9781394354016
Publisher John Wiley & Sons Inc
Imprint Wiley-IEEE Press
Country of Manufacture GB
Country of Publication GB
Publication Date Dec 28th, 2025
Print length 400 Pages
Ksh 20,000.00
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An expert discussion of intelligent optimization control in complex industrial processes In A Hardware-in-Loop Digital Twin Approach to Intelligent Optimization of Municipal Solid Waste Incineration, a team of distinguished researchers delivers an innovative new approach to integrating virtual mechanism data generated through coupled numerical simulation and orthogonal experimental design with real historical data. The book explains how to create a heterogenous ensemble prediction model for carbon monoxide emissions in municipal solid waste incineration (MSWI) processes. >The authors focus on intelligent optimization control of MSWI processes based on hardware-in-loop DT platforms. They demonstrate AI-driven modeling, control, optimization algorithms in real-world applications, including virtual-real data hybrid-driven deep modeling and intelligent optimal controls based on multiple objectives. Additional topics include: A thorough introduction to numerical simulation modeling of whole industrial processesComprehensive explorations of the design, implementation, and validation of hardware-in-loop digital twin platformsPractical discussions of AI-driven modeling, control, and optimizationFulsome descriptions of the skills required to address challenges posed by complex industrial processes Perfect for environmental engineers and researchers, A Hardware-in-Loop Digital Twin Approach to Intelligent Optimization of Municipal Solid Waste Incineration will also benefit MSWI plant operators and managers, as well as AI and machine learning researchers and developers of environmental monitoring and control systems.

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