Nguyen van thuc (30 risultati)
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Paperback. Condizione: Brand New. 330 pages. 6.14x0.75x9.21 inches. In Stock.
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Condizione: New. Tien V.T. Nguyen, a member of the IEEE, is a highly accomplished individual with an impressive educational background. He obtained a master s degree in mechanical engineering and linguistics from prestigious institutions such as Viet Nam National .
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Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
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EUR 109,00
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Taschenbuch. Condizione: Neu. Neuware - As multicriteria decision-making (MCDM) continues to grow and evolve, machine learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide researchers, practitioners, and students interested in…the intersection of ML and MCDM for optimal design. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is a comprehensive resource that bridges the gap between ML and MCDM. It offers a practical approach by demonstrating the application of ML and MCDM algorithms to real-world problems. Through case studies and examples, it showcases the effectiveness of these techniques in optimal design. The book also provides a comparative analysis of conventional MCDM algorithms and machine learning techniques, enabling readers to make informed decisions about their use in different scenarios. It also delves into emerging trends, providing insights into future directions and potential opportunities. The book covers a wide range of topics, including the definition of optimal design, MCDM algorithms, supervised and unsupervised ML techniques, deep learning techniques, and more, making it a valuable resource for professionals and researchers in various fields. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is designed for professionals, researchers, and practitioners in engineering, computer science, sustainability, and related fields. It is also a valuable resource for students and academics who wish to expand their knowledge of machine learning applications in multicriteria decision-making. By offering a blend of theoretical insights and practical examples, this guide aims to inspire further research and application of machine learning in multidimensional decision-making environments.
Multi-criteria Decision-making and Optimum Design With Machine Learning : A Practical Guide
Nguyen, Van Thanh Tien (EDT); Vo, Nhut T. M. (EDT); Truong, Van Chinh (EDT); Nguyen, Van-thuc (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Condizione: As New. Unread book in perfect condition.
Multi-criteria Decision-making and Optimum Design With Machine Learning : A Practical Guide
Nguyen, Van Thanh Tien (EDT); Vo, Nhut T. M. (EDT); Truong, Van Chinh (EDT); Nguyen, Van-thuc (EDT)
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Da: GreatBookPrices, Columbia, MD, U.S.A.GreatBookPrices
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Da: California Books, Miami, FL, U.S.A.California Books
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Multi-criteria Decision-making and Optimum Design With Machine Learning : A Practical Guide
Nguyen, Van Thanh Tien (EDT); Vo, Nhut T. M. (EDT); Truong, Van Chinh (EDT); Nguyen, Van-thuc (EDT)
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
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EUR 192,47
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Condizione: New.
Multi-criteria Decision-making and Optimum Design With Machine Learning : A Practical Guide
Nguyen, Van Thanh Tien (EDT); Vo, Nhut T. M. (EDT); Truong, Van Chinh (EDT); Nguyen, Van-thuc (EDT)
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Da: GreatBookPricesUK, Woodford Green, Regno UnitoGreatBookPricesUK
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EUR 182,98
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Condizione: New.
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Da: PBShop.store US, Wood Dale, IL, U.S.A.PBShop.store US
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Da: PBShop.store UK, Fairford, GLOS, Regno UnitoPBShop.store UK
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HRD. Condizione: New. New Book. Shipped from UK. Established seller since 2000.
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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New.
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Da: THE SAINT BOOKSTORE, Southport, Regno UnitoTHE SAINT BOOKSTORE
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Hardback. Condizione: New. New copy - Usually dispatched within 4 working days.
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- Edizione Internazionale
Da: UK BOOKS STORE, London, LONDO, Regno UnitoUK BOOKS STORE
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Condizione: New Books. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requeste…d if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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EUR 264,05
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Hardcover. Condizione: Brand New. 424 pages. 9.18x6.12x9.21 inches. In Stock.
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- Print on Demand
Da: moluna, Greven, Germaniamoluna
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EUR 31,27
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Condizione: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dao Chanh ThucMain Author: Dao Chanh ThucPhysical Education Deparment, An Giang University, VIETNAM. Author 2: Nguyen Van TangHo Chi Minh City University Of Sport, Ho Chi Minh Ci.
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- Print on Demand
Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 84,19
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Paperback. Condizione: new. Paperback. As multicriteria decision-making (MCDM) continues to grow and evolve, machine learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide researchers, practitioners, and students interested in t…he intersection of ML and MCDM for optimal design. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is a comprehensive resource that bridges the gap between ML and MCDM. It offers a practical approach by demonstrating the application of ML and MCDM algorithms to real-world problems. Through case studies and examples, it showcases the effectiveness of these techniques in optimal design. The book also provides a comparative analysis of conventional MCDM algorithms and machine learning techniques, enabling readers to make informed decisions about their use in different scenarios. It also delves into emerging trends, providing insights into future directions and potential opportunities. The book covers a wide range of topics, including the definition of optimal design, MCDM algorithms, supervised and unsupervised ML techniques, deep learning techniques, and more, making it a valuable resource for professionals and researchers in various fields. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is designed for professionals, researchers, and practitioners in engineering, computer science, sustainability, and related fields. It is also a valuable resource for students and academics who wish to expand their knowledge of machine learning applications in multicriteria decision-making. By offering a blend of theoretical insights and practical examples, this guide aims to inspire further research and application of machine learning in multidimensional decision-making environments. As Multi-Criteria Decision-Making (MCDM) continues to grow and evolve, Machine Learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide researchers, practitioners, and students interested in the intersection of ML and MCDM for optimal design. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 90,38
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Paperback. Condizione: new. Paperback. As multicriteria decision-making (MCDM) continues to grow and evolve, machine learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide researchers, practitioners, and students interested in t…he intersection of ML and MCDM for optimal design. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is a comprehensive resource that bridges the gap between ML and MCDM. It offers a practical approach by demonstrating the application of ML and MCDM algorithms to real-world problems. Through case studies and examples, it showcases the effectiveness of these techniques in optimal design. The book also provides a comparative analysis of conventional MCDM algorithms and machine learning techniques, enabling readers to make informed decisions about their use in different scenarios. It also delves into emerging trends, providing insights into future directions and potential opportunities. The book covers a wide range of topics, including the definition of optimal design, MCDM algorithms, supervised and unsupervised ML techniques, deep learning techniques, and more, making it a valuable resource for professionals and researchers in various fields. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is designed for professionals, researchers, and practitioners in engineering, computer science, sustainability, and related fields. It is also a valuable resource for students and academics who wish to expand their knowledge of machine learning applications in multicriteria decision-making. By offering a blend of theoretical insights and practical examples, this guide aims to inspire further research and application of machine learning in multidimensional decision-making environments. As Multi-Criteria Decision-Making (MCDM) continues to grow and evolve, Machine Learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide researchers, practitioners, and students interested in the intersection of ML and MCDM for optimal design. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 107,19
EUR 32,04 spedizioneSpedito da Australia a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. As multicriteria decision-making (MCDM) continues to grow and evolve, machine learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide researchers, practitioners, and students interested in t…he intersection of ML and MCDM for optimal design. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is a comprehensive resource that bridges the gap between ML and MCDM. It offers a practical approach by demonstrating the application of ML and MCDM algorithms to real-world problems. Through case studies and examples, it showcases the effectiveness of these techniques in optimal design. The book also provides a comparative analysis of conventional MCDM algorithms and machine learning techniques, enabling readers to make informed decisions about their use in different scenarios. It also delves into emerging trends, providing insights into future directions and potential opportunities. The book covers a wide range of topics, including the definition of optimal design, MCDM algorithms, supervised and unsupervised ML techniques, deep learning techniques, and more, making it a valuable resource for professionals and researchers in various fields. Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is designed for professionals, researchers, and practitioners in engineering, computer science, sustainability, and related fields. It is also a valuable resource for students and academics who wish to expand their knowledge of machine learning applications in multicriteria decision-making. By offering a blend of theoretical insights and practical examples, this guide aims to inspire further research and application of machine learning in multidimensional decision-making environments. As Multi-Criteria Decision-Making (MCDM) continues to grow and evolve, Machine Learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide researchers, practitioners, and students interested in the intersection of ML and MCDM for optimal design. 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.
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- Print on Demand
Da: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, GermaniaBuchWeltWeit Ludwig Meier e.K.
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 161,40
EUR 23,00 spedizioneSpedito da Germania a U.S.A.Quantità: 2 disponibili
Buch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -As multicriteria decision-making (MCDM) continues to grow and evolve, machine learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide res…earchers, practitioners, and students interested in the intersection of ML and MCDM for optimal design.Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guideis a comprehensive resource that bridges the gap between ML and MCDM. It offers a practical approach by demonstrating the application of ML and MCDM algorithms to real-world problems. Through case studies and examples,it showcases the effectiveness of these techniques in optimal design.The book also providesa comparative analysis of conventional MCDM algorithms and machine learning techniques,enabling readersto make informed decisions about their use in different scenarios. It also delves into emerging trends, providing insights into future directions and potential opportunities.The book covers awide range of topics, including the definition of optimal design, MCDM algorithms, supervised and unsupervised ML techniques, deep learning techniques, and more, making it a valuable resource for professionals and researchers in various fields.Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is designed for professionals, researchers, and practitioners in engineering, computer science, sustainability, and related fields. It isalso a valuable resource for students and academics who wish to expand their knowledge of machine learning applications in multicriteria decision-making. By offering a blend of theoretical insights and practical examples, this guide aims to inspire further research and application of machine learning in multidimensional decision-making environments. 362 pp. Englisch.
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- Print on Demand
Da: AHA-BUCH GmbH, Einbeck, GermaniaAHA-BUCH GmbH
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 161,40
EUR 63,54 spedizioneSpedito da Germania a U.S.A.Quantità: 1 disponibili
Buch. Condizione: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As multicriteria decision-making (MCDM) continues to grow and evolve, machine learning (ML) techniques have become increasingly important in finding efficient and effective solutions to complex problems. This book is intended to guide research…ers, practitioners, and students interested in the intersection of ML and MCDM for optimal design.Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guideis a comprehensive resource that bridges the gap between ML and MCDM. It offers a practical approach by demonstrating the application of ML and MCDM algorithms to real-world problems. Through case studies and examples,it showcases the effectiveness of these techniques in optimal design.The book also providesa comparative analysis of conventional MCDM algorithms and machine learning techniques,enabling readersto make informed decisions about their use in different scenarios. It also delves into emerging trends, providing insights into future directions and potential opportunities.The book covers awide range of topics, including the definition of optimal design, MCDM algorithms, supervised and unsupervised ML techniques, deep learning techniques, and more, making it a valuable resource for professionals and researchers in various fields.Multi-Criteria Decision-Making and Optimum Design with Machine Learning: A Practical Guide is designed for professionals, researchers, and practitioners in engineering, computer science, sustainability, and related fields. It isalso a valuable resource for students and academics who wish to expand their knowledge of machine learning applications in multicriteria decision-making. By offering a blend of theoretical insights and practical examples, this guide aims to inspire further research and application of machine learning in multidimensional decision-making environments.
