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Artificial Intelligence for Fault Detection and Diagnosis | Buch | Englisch | 2025 | MDPI AG | EAN 9783725849130 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. Codice articolo 133845518
Titolo: Artificial Intelligence for Fault Detection ...
Casa editrice: MDPI AG
Data di pubblicazione: 2025
Legatura: Buch
Condizione: Neu
Da: PBShop.store UK, Fairford, GLOS, Regno Unito
HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L1-9783725849130
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Da: PBShop.store US, Wood Dale, IL, U.S.A.
HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Codice articolo L1-9783725849130
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Da: CitiRetail, Stevenage, Regno Unito
Hardcover. Condizione: new. Hardcover. Fault detection and diagnosis (FDD) is an important task in manufacturing and mechatronic systems for reducing costs and improving productivity. Traditionally, the states of machines and their faults are manually checked, a process which is time-consuming and expensive. Therefore, it is desirable to develop intelligent systems to achieve automatic FDD. Artificial intelligence as a concept covers a wide range of algorithms that mimic the human mind, thinking and acting like humans to solve important tasks in different fields. In recent years, many AI algorithms have been applied to FDD, including data processing, feature analysis, and classification. Typical methods include deep neural networks, long short-term memory, convolutional neural networks, random forest, and evolutionary computation. However, the potential of AI has not been comprehensively investigated in FDD. This remains a challenging task due to many factors, such as changeable equipment working states, incomplete information, a lack of sufficient training data, complex relationships between faults and symptoms, imbalanced data, and the requirement of having domain knowledge. This reprint is a collection of research regarding AI techniques applied to various FDD tasks. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9783725849130
Quantità: 1 disponibili
Da: AussieBookSeller, Truganina, VIC, Australia
Hardcover. Condizione: new. Hardcover. Fault detection and diagnosis (FDD) is an important task in manufacturing and mechatronic systems for reducing costs and improving productivity. Traditionally, the states of machines and their faults are manually checked, a process which is time-consuming and expensive. Therefore, it is desirable to develop intelligent systems to achieve automatic FDD. Artificial intelligence as a concept covers a wide range of algorithms that mimic the human mind, thinking and acting like humans to solve important tasks in different fields. In recent years, many AI algorithms have been applied to FDD, including data processing, feature analysis, and classification. Typical methods include deep neural networks, long short-term memory, convolutional neural networks, random forest, and evolutionary computation. However, the potential of AI has not been comprehensively investigated in FDD. This remains a challenging task due to many factors, such as changeable equipment working states, incomplete information, a lack of sufficient training data, complex relationships between faults and symptoms, imbalanced data, and the requirement of having domain knowledge. This reprint is a collection of research regarding AI techniques applied to various FDD tasks. 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. Codice articolo 9783725849130
Quantità: 1 disponibili
Da: Books Puddle, New York, NY, U.S.A.
Condizione: New. Codice articolo 26404722848
Quantità: 4 disponibili
Da: Majestic Books, Hounslow, Regno Unito
Condizione: New. Print on Demand. Codice articolo 409480063
Quantità: 4 disponibili
Da: Biblios, Frankfurt am main, HESSE, Germania
Condizione: New. PRINT ON DEMAND. Codice articolo 18404722858
Quantità: 4 disponibili