Buabeng Albert (8 results)
- Softcover
Seller: Books Puddle, New York, NY, U.S.A.Books Puddle
Contact seller4-star sellerCondition: New
US$ 116.86
US$ 3.99 shippingShips within U.S.A.Quantity: 4 available
Condition: New.
- Softcover
Seller: moluna, Greven, , Germanymoluna
Contact seller5-star sellerCondition: New
US$ 75.84
US$ 51.21 shippingShips from Germany to U.S.A.Quantity: Over 20 available
Condition: New.
- Softcover
Seller: preigu, Osnabrück, Germanypreigu
Contact seller5-star sellerCondition: New
US$ 83.16
US$ 79.66 shippingShips from Germany to U.S.A.Quantity: 5 available
Taschenbuch. Condition: Neu. Intelligent Predictive Maintenance Frameworks for Fault Classification | Hybridising Machine Learning Techniques | Albert Buabeng (u. a.) | Taschenbuch | Englisch | 2023 | LAP LAMBERT Academic Publishing | EAN 9786206752738 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landst…r. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2023 2023
- Softcover
- Print on Demand
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, , GermanyBuchWeltWeit Ludwig Meier e.K.
Contact seller5-star sellerCondition: New
US$ 99.52
US$ 26.17 shippingShips from Germany to U.S.A.Quantity: 2 available
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -With the rising demand for complex, integrated and autonomous systems in the field of engineering, efficient and versatile Predictive Maintenance (PdM) frameworks have become a requirement for monitoring the health status of these s…ystems since safety, reliability and optimum asset utilisation, are key issues. However, due to the continuously changing dynamics of industrial operations, the data recorded for developing PdM frameworks are often high-dimensional and characterised by undesirable features such as high level of uncertainty, class imbalance and multiclass among others. These undesirables limit the efficiency of existing PdM frameworks in producing desirable results. For these reasons, this book has proposed three hybrid and novel PdM frameworks capable of handling such undesirable features through the hybridisation of machine learning techniques. The proposed hybrid frameworks advance the field of PdM by improving the accuracy of fault diagnosis as the issue of undesirable features impedes the ability of machine learning algorithms to produce desired results. 244 pp. Englisch.
- Softcover
- Print on Demand
Seller: Majestic Books, Hounslow, , United KingdomMajestic Books
Contact seller4-star sellerCondition: New
US$ 119.06
US$ 8.58 shippingShips from United Kingdom to U.S.A.Quantity: 4 available
Condition: New. Print on Demand.
- Softcover
- Print on Demand
Seller: Biblios, frankfurt am main, HESSE, GermanyBiblios
Contact seller4-star sellerCondition: New
US$ 126.17
US$ 11.32 shippingShips from Germany to U.S.A.Quantity: 4 available
Condition: New. PRINT ON DEMAND.
Language: English
Published by LAP LAMBERT Academic Publishing Jul 2023 2023
- Softcover
- Print on Demand
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
Contact seller5-star sellerCondition: New
US$ 99.52
US$ 68.28 shippingShips from Germany to U.S.A.Quantity: 1 available
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -With the rising demand for complex, integrated and autonomous systems in the field of engineering, efficient and versatile Predictive Maintenance (PdM) frameworks have become a requirement for monitoring the health status of these syste…ms since safety, reliability and optimum asset utilisation, are key issues. However, due to the continuously changing dynamics of industrial operations, the data recorded for developing PdM frameworks are often high-dimensional and characterised by undesirable features such as high level of uncertainty, class imbalance and multiclass among others. These undesirables limit the efficiency of existing PdM frameworks in producing desirable results. For these reasons, this book has proposed three hybrid and novel PdM frameworks capable of handling such undesirable features through the hybridisation of machine learning techniques. The proposed hybrid frameworks advance the field of PdM by improving the accuracy of fault diagnosis as the issue of undesirable features impedes the ability of machine learning algorithms to produce desired results.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 244 pp. Englisch.
- Softcover
- Print on Demand
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
Contact seller5-star sellerCondition: New
US$ 100.71
US$ 70.45 shippingShips from Germany to U.S.A.Quantity: 1 available
Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - With the rising demand for complex, integrated and autonomous systems in the field of engineering, efficient and versatile Predictive Maintenance (PdM) frameworks have become a requirement for monitoring the health status of these system…s since safety, reliability and optimum asset utilisation, are key issues. However, due to the continuously changing dynamics of industrial operations, the data recorded for developing PdM frameworks are often high-dimensional and characterised by undesirable features such as high level of uncertainty, class imbalance and multiclass among others. These undesirables limit the efficiency of existing PdM frameworks in producing desirable results. For these reasons, this book has proposed three hybrid and novel PdM frameworks capable of handling such undesirable features through the hybridisation of machine learning techniques. The proposed hybrid frameworks advance the field of PdM by improving the accuracy of fault diagnosis as the issue of undesirable features impedes the ability of machine learning algorithms to produce desired results.
