Modeling of the Whole Lifecycle Dioxins for Municipal Solid Waste Incineration

Jian Tang is a Professor at Beijing University of Technology and Deputy Director of Beijing Laboratory of Smart Environmental Protection. He received his Ph.D. from Northeastern University, Shenyang, China, in 2012. He has authorized over 50 US/Chinese invention patents and obtained over 30 software copyrights. He is a senior member of IEEE.Loai Aljerf is a Professor at Damascus University. He has created partnerships and memberships in prestigious organizations, including the Advances in Cleaner Production Network, the German Chemical Society e.V. (GDCh), the Asian Chemical Society, and the American University of Beirut.Junfei Qiao is a Professor with the Beijing University of Technology and Director of Beijing Laboratory of Smart Environmental Protection, Beijing, China. He received his Ph.D. from Northeastern University, Shenyang, China, in 1998. He is a member of several government bodies and director of several national committees in China. He is a senior member of IEEE.

• 1. Introduction Part I: Dioxins characteristics analysis of in MSWI process 2. MSWI Process Description for Dioxins 3. Investigation on Dioxins Emission Characteristic during Complete Maintenance Operating Period 4. Assessment of Dioxins Formation and Emission Characteristics for One Year Part II: Dioxins with numerical simulation modelling 5. Non-Manipulated Variable Modeling of Solid-Phase Combustion in the Furnace 6. Unveiling Dioxin Dynamics: A Whole-Process Simulation Model Part III: Dioxins with AI driven detection modeling and risk warning 7. Multi-Scale Modeling Using Gan And Deep Forest Regression for Dioxin Emission Concentration 8. Hybrid Simulator-Based Mechanism and Data-Driven Modeling for Multi-Demand Dioxin Emissions Concentration 9. Multimodal Data-Driven Interpretable Deep Modeling Approach of Dioxins Generation Concentration 10. AI-Based Tree Modeling for Multi-Point Dioxin Concentrations 11. Virtual Sample Generation Method Based on Generative Adversarial Fuzzy Neural Network for Dioxin Emission Risk Warning 12. Summary and outlook