Description: Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems by Ruqiang Yan, Zhibin Zhao Estimated delivery 3-12 business days Format Hardcover Condition Brand New Description The book aims to highlight the potential of Deep Learning (DL)-based methods in Intelligent Fault Diagnosis (IFD), along with their benefits and contributions. Publisher Description The book aims to highlight the potential of deep learning (DL)-enabled methods in intelligent fault diagnosis (IFD), along with their benefits and contributions.The authors first introduce basic applications of DL-enabled IFD, including auto-encoders, deep belief networks, and convolutional neural networks. Advanced topics of DL-enabled IFD are also explored, such as data augmentation, multi-sensor fusion, unsupervised deep transfer learning, neural architecture search, self-supervised learning, and reinforcement learning. Aiming to revolutionize the nature of IFD, Deep Neural Networks-Enabled Intelligent Fault Diangosis of Mechanical Systems contributes to improved efficiency, safety, and reliability of mechanical systems in various industrial domains.The book will appeal to academic researchers, practitioners, and students in the fields of intelligent fault diagnosis, prognostics and health management, and deep learning. Author Biography Ruqiang Yan is a professor at the School of Mechanical Engineering, Xian Jiaotong University. His research interests include data analytics, AI, and energy-efficient sensing and sensor networks for the condition monitoring and health diagnosis of large-scale, complex, dynamical systems.Zhibin Zhao is an assistant professor at the School of Mechanical Engineering, Xian Jiaotong University. His research interests include sparse signal processing and machine learning, especially deep learning for machine fault detection, diagnosis, and prognosis. Details ISBN 1032752378 ISBN-13 9781032752372 Title Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems Author Ruqiang Yan, Zhibin Zhao Format Hardcover Year 2024 Pages 206 Publisher Taylor & Francis Ltd GE_Item_ID:160036390; About Us Grand Eagle Retail is the ideal place for all your shopping needs! With fast shipping, low prices, friendly service and over 1,000,000 in stock items - you're bound to find what you want, at a price you'll love! Shipping & Delivery Times Shipping is FREE to any address in USA. Please view eBay estimated delivery times at the top of the listing. Deliveries are made by either USPS or Courier. We are unable to deliver faster than stated. International deliveries will take 1-6 weeks. NOTE: We are unable to offer combined shipping for multiple items purchased. This is because our items are shipped from different locations. Returns If you wish to return an item, please consult our Returns Policy as below: Please contact Customer Services and request "Return Authorisation" before you send your item back to us. Unauthorised returns will not be accepted. Returns must be postmarked within 4 business days of authorisation and must be in resellable condition. Returns are shipped at the customer's risk. We cannot take responsibility for items which are lost or damaged in transit. For purchases where a shipping charge was paid, there will be no refund of the original shipping charge. Additional Questions If you have any questions please feel free to Contact Us. Categories Baby Books Electronics Fashion Games Health & Beauty Home, Garden & Pets Movies Music Sports & Outdoors Toys
Price: 118.99 USD
Location: Fairfield, Ohio
End Time: 2024-11-14T04:18:49.000Z
Shipping Cost: 0 USD
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Restocking Fee: No
Return shipping will be paid by: Buyer
All returns accepted: Returns Accepted
Item must be returned within: 30 Days
Refund will be given as: Money Back
ISBN-13: 9781032752372
Book Title: Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mecha
Number of Pages: 206 Pages
Publication Name: Deep Neural Networks-Enabled Intelligent Fault Diagnosis of Mechanical Systems
Language: English
Publisher: Taylor & Francis Group
Subject: Engineering (General), Intelligence (Ai) & Semantics, Mechanical, Neural Networks
Publication Year: 2024
Type: Textbook
Item Weight: 16 Oz
Subject Area: Computers, Technology & Engineering
Author: Zhibin Zhao, Ruqiang Yan
Item Length: 10 in
Item Width: 7 in
Format: Hardcover
