Read more
List of contents
Part I : Industrial Solid Ashes
1. Background of industrial soild ashes
2. Current strategies for solid ash management and recycling
Part II: Machine Learning Modelling
3. Historical background of ML
4. Introduction to ML techniques
5. ML modelling methodology
Part III : Application of ML in solid ash management and recycling
6. Physiochemical properties of solid ash and clustering analysis
7. Accurate estimation of the solid ash generation
8. Evaluation of the trace elements pollution of coal fly ash using ML techniques
9. Metal recovery prediction using random forest
10. Rapid identification of amourphous phases in solid ash
11. Reactivity classification of solid ash using ML techniques
12. Forecast of uniaxial compressive strength of solid ash-based concrete
Part IV : Future perspectives and challenges to adopting ML in solid ash management and recycling
13. Future perspective and opportunities in ML for solid ash management and recycling
14. Challenges to adopting ML in solid ash management and recycling
About the author
Chongchong Qi is a professor in School of Resources and Safety Engineering at the Central South University. Prof. Qi’s research and writing is focused in the areas of solids waste management in the mining industry, innovative strategies for solids waste reusing and recycling, artificial intelligence, and its applications in the mining. With more than 70 high-quality SCI papers being published, Prof. Qi announces the idea of ‘intelligent design system for backfill mining’. He serves on various international committees and works as the editorial board member for three SCI journals. Prof. Qi also received various funds home and abroad for the innovative application of AI in the mining industry.
