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Machine Learning Applications in Industrial Solid Ash begins with fundamentals in solid ash, covering the status of solid ash generation and management. The book moves on to foundational knowledge on ML in solid ash management, which provides a brief introduction of ML for solid ash applications. The reference then goes on to discuss ML approaches currently used to address problems in solid ash management and recycling, including solid ash generation, clustering analysis, origin identification, reactivity prediction, leaching potential modelling and metal recovery evaluation, etc. Finally, potential future trends and challenges in the field are discussed. Offering the ability to process large or complex datasets, machine learning (ML) holds huge potential to reshape the whole status for solid ash management and recycling. This book is the first published book about ML in solid ash management and recycling. It highlights fundamental knowledge and recent advances in this topic, offering readers new insight into how these tools can be utilized to enhance their own work.
Managing Mining and Minerals Processing Wastes: Concepts, Design and Applications presents fundamental knowledge in waste management in mining and minerals processing and summarizes recent advances. The book offers readers insights into innovative ways to manage waste in the mining and minerals industry. Sections cover a brief introduction to this topic and an explanation of waste generation, and how to manage the six types of waste, including waste rock, mill tailings, coal refuse and coal fly ash, quarry waste, metallurgical slugs and washery rejects. The title then emphasizes the management of hazardous waste, the acid mine drainage and the lifecycle assessment of waste management. Finally, the book considers current and emerging challenges. This publication offers a comprehensive background to waste management in mining and minerals processing and a summary of recent advances and innovative strategies for managing each kind of waste.
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