An expert discussion of intelligent optimization control in complex industrial processes
In A Hardware-in-Loop Digital Twin Approach for Intelligent Optimization of Municipal Solid Waste Incineration: AI and Its Application to Complex Industrial Processes, 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:
Perfect for environmental engineers and researchers, A Hardware-in-Loop Digital Twin Approach for 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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Jian Tang, PhD, is a Professor and Researcher with the Department of Artificial Intelligence and Automation in the Faculty of Information Technology at the Beijing University of Technology.
Wen Yu, PhD, is a Professor and Head of Department of the Departamento de Control Automatico at CINVESTAV-IPN (National Polytechnic Institute) in Mexico City, Mexico.
Junfei Qiao, PhD, is a Professor with the Beijing University of Technology and Director of Beijing Laboratory of Smart Environmental Protection in Beijing, China.
An expert discussion of intelligent optimization control in complex industrial processes
In A Hardware-in-Loop Digital Twin Approach for Intelligent Optimization of Municipal Solid Waste Incineration: AI and Its Application to Complex Industrial Processes, 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:
Perfect for environmental engineers and researchers, A Hardware-in-Loop Digital Twin Approach for 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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