Machine Learning Applications In Industrial Solid Ash

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Machine Learning Applications in Industrial Solid Ash

Machine Learning Applications in Industrial Solid Ash
Author :
Publisher : Elsevier
Total Pages : 315
Release :
ISBN-10 : 9780443155253
ISBN-13 : 0443155259
Rating : 4/5 (259 Downloads)

Book Synopsis Machine Learning Applications in Industrial Solid Ash by : Chongchong Qi

Download or read book Machine Learning Applications in Industrial Solid Ash written by Chongchong Qi and published by Elsevier. This book was released on 2023-12-01 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Machine Learning for Solid Ash Management and Recycling is, as far as the author knows, the first published book about ML in solid ash management and recycling. This book 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. The reference 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. - Helps readers increase their existing knowledge on data mining and ML - Teaches how to apply ML techniques that work best in solid ash management and recycling through providing illustrative examples and complex practice solutions - Provides an accessible introduction to the current state and future possibilities for ML in solid ash management and recycling


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