Machine Learning Applications in Industrial Solid Ash

Name: Machine Learning Applications in Industrial Solid Ash
Brand: Elsevier Inc
SKU: 9780443155246
Price: 4787 CZK
Availability: InStock

Autor: Chongchong Qi

Jazyk:

Vazba: Brožovaná

Vydavatel: Elsevier Inc

Dostupnost: Skladem u dodavatele

Odesíláme za 10-18 dnů

4 787 Kč

Offering the ability to process large or complex datasets, machine learning (ML) holds huge potentia...

Informace o knize

Autor

Chongchong Qi

Jazyk

Angličtina

Vazba

Kniha - Brožovaná

Vydáno

2024

Stránek

270

EAN

9780443155246

Enbook ID

43613886

Vydavatel

Elsevier Inc

Hmotnost

421

Rozměry

152 x 229

Kompletní popis

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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