Engineering applications demand forecasting (13 resultados)

Condición: New.

Condición: New.

Condición: New.

Condición: New.

Condición: New. Dr. Bhargav Appasani received the Ph.D. (Engg.) degree from Birla Institute of Technology, Mesra, India. He is currently an Associate Professor with the School of Electronics Engineering, KIIT University, Bhubaneswar, India. He has published more .

Hardcover. Condición: Brand New. 296 pages. 9.18x6.12x9.45 inches. In Stock.

Hardcover. Condición: new. Hardcover. Engineering Applications of AI for Demand Forecasting explores how Artificial Intelligence enhances prediction accuracy across modern engineering systems. As industries move toward Industry 4.0, the book highlights the role of AI in processing large, dynamic datasets for smarter decision-making. This book brings together contemporary research that demonstrates AIs ability to enhance precision, efficiency, and adaptability in diverse forecasting environments. By covering cybersecurity analytics, anomaly detection, logistics forecasting, sustainable supply chain management, and predictive maintenance, it demonstrates AIs versatility in complex environments. The book also showcases AI applications in renewable energy forecasting, peak load prediction, smart meter analytics, and prosumer-driven demand modeling. Combining theory with practical case studies, it serves as a valuable resource for engineers, researchers, practitioners, and students. Engineering Applications of AI for Demand Forecasting explores how Artificial Intelligence enhances prediction accuracy across modern engineering systems. As industries move toward Industry 4.0, the book highlights the role of AI in processing large, dynamic datasets for smarter decision-making. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condición: new. Hardcover. Engineering Applications of AI for Demand Forecasting explores how Artificial Intelligence enhances prediction accuracy across modern engineering systems. As industries move toward Industry 4.0, the book highlights the role of AI in processing large, dynamic datasets for smarter decision-making. This book brings together contemporary research that demonstrates AIs ability to enhance precision, efficiency, and adaptability in diverse forecasting environments. By covering cybersecurity analytics, anomaly detection, logistics forecasting, sustainable supply chain management, and predictive maintenance, it demonstrates AIs versatility in complex environments. The book also showcases AI applications in renewable energy forecasting, peak load prediction, smart meter analytics, and prosumer-driven demand modeling. Combining theory with practical case studies, it serves as a valuable resource for engineers, researchers, practitioners, and students. Engineering Applications of AI for Demand Forecasting explores how Artificial Intelligence enhances prediction accuracy across modern engineering systems. As industries move toward Industry 4.0, the book highlights the role of AI in processing large, dynamic datasets for smarter decision-making. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

HRD. Condición: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condición: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

Hardcover. Condición: new. Hardcover. Engineering Applications of AI for Demand Forecasting explores how Artificial Intelligence enhances prediction accuracy across modern engineering systems. As industries move toward Industry 4.0, the book highlights the role of AI in processing large, dynamic datasets for smarter decision-making. This book brings together contemporary research that demonstrates AIs ability to enhance precision, efficiency, and adaptability in diverse forecasting environments. By covering cybersecurity analytics, anomaly detection, logistics forecasting, sustainable supply chain management, and predictive maintenance, it demonstrates AIs versatility in complex environments. The book also showcases AI applications in renewable energy forecasting, peak load prediction, smart meter analytics, and prosumer-driven demand modeling. Combining theory with practical case studies, it serves as a valuable resource for engineers, researchers, practitioners, and students. Engineering Applications of AI for Demand Forecasting explores how Artificial Intelligence enhances prediction accuracy across modern engineering systems. As industries move toward Industry 4.0, the book highlights the role of AI in processing large, dynamic datasets for smarter decision-making. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Buch. Condición: Neu. Engineering Applications of AI for Demand Forecasting | Bhargav Appasani (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | CRC Press | EAN 9781032863832 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Engineering Applications of AI for Demand Forecasting explores how Artificial Intelligence enhances prediction accuracy across modern engineering systems. As industries move toward Industry 4.0, the book highlights the role of AI in processing large, dynamic datasets for smarter decision-making. This book brings together contemporary research that demonstrates AI's ability to enhance precision, efficiency, and adaptability in diverse forecasting environments. By covering cybersecurity analytics, anomaly detection, logistics forecasting, sustainable supply chain management, and predictive maintenance, it demonstrates AI's versatility in complex environments. The book also showcases AI applications in renewable energy forecasting, peak load prediction, smart meter analytics, and prosumer-driven demand modeling. Combining theory with practical case studies, it serves as a valuable resource for engineers, researchers, practitioners, and students.…