Debiao meng (38 risultati)

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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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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Multidisciplinary Design Optimization Of Complex Structures Under Uncertainty
Meng, Debiao Zhu, Shun-Peng (University Of Electronic Science And Technology Of China, China)
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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Multidisciplinary Design Optimization of Complex Structures Under Uncertainty
Debiao Meng|Shun-Peng Zhu (University of Electronic Science and Technology of China, China)
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Da: moluna, Greven, Germaniamoluna
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Condizione: New. Debiao Meng is an associate professor in the School of Mechanical and Electrical Engineering at the University of Electronic Science and Technology of China, China.Shun-Peng Zhu is a professor in the School of Mechanical and Electric.

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Da: Books From California, Simi Valley, CA, U.S.A.Books From California
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hardcover. Condizione: Fine.

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Da: California Books, Miami, FL, U.S.A.California Books
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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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Condizione: New. pp. 348.

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Da: Ria Christie Collections, Uxbridge, Regno UnitoRia Christie Collections
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Da: Books Puddle, New York, NY, U.S.A.Books Puddle
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Condizione: New. pp. 348 1st edition NO-PA16APR2015-KAP.

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Da: Biblios, frankfurt am main, HESSE, GermaniaBiblios
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Condizione: New. pp. 348.

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Da: Revaluation Books, Exeter, Regno UnitoRevaluation Books
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Hardcover. Condizione: Brand New. 352 pages. 9.25x6.25x1.00 inches. In Stock.

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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Hardcover. Condizione: new. Hardcover. This Reprint contains all of the articles that were accepted and published in the Special Issue of Mathematics titled "Modeling and Optimization of Complex Engineering Systems under Uncertainties". It offers a comprehensive overview of the current state of the art in reliability engineering… and applied mathematics. The research highlights a fundamental transition in engineering design and control, moving away from static safety factors toward dynamic, probabilistic, and data-driven frameworks. We have observed that hybrid optimization algorithms, such as the coupled Simulated Annealing and Particle Swarm Optimization, offer superior efficiency in navigating high-dimensional design spaces. We have seen that Scientific Machine Learning can be made robust to uncertainty through Bayesian inference, ensuring that soft sensors and control models remain trustworthy in critical applications. Furthermore, the successful application of these methods to diverse fields, including tunnel engineering, wind energy, structural health monitoring, and construction safety, confirms the universal relevance of uncertainty quantification. We hope that the methodologies and findings presented in this volume will serve as a foundation for future inquiries and inspire researchers to further explore the intricate dynamics of complex engineering systems. 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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Da: Grand Eagle Retail, Bensenville, IL, U.S.A.Grand Eagle Retail
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Paperback. Condizione: new. Paperback. In the realm of engineering structures design, the inevitability of uncertainties poses a significant challenge. Uncertainty-Based Multidisciplinary Design and Optimization (UBMDO) stands out for its dual ability to precisely quantify the impact of uncertain variables and harness the potent…ial of multidisciplinary design and optimization, thereby attracting considerable attention. From basic theory to advanced applications, this book helps readers achieve more efficient and reliable design optimization in complex systems through rich case studies and practical technical guidance.The book systematically expounds the fundamental theories and methods of UBMDO, encompassing crucial techniques such as uncertainty modeling, sensitivity analysis, approximate modeling, and uncertainty-based optimization. It also introduces various uncertainty analysis methods, such as stochastic, non-probabilistic, and hybrid approaches, aiding readers in comprehending and managing uncertainty within systems. Through diverse practical engineering cases in fields like machinery, aerospace, and energy, it illustrates the specific application and implementation process of the UBMDO method. Rich graphics, algorithms, and simulation results augment the practicality and applicability of the theoretical knowledge. Furthermore, it explores in depth the future development trends and challenges of UBMDO, sparking innovative thinking and research interests among readers in this field.Multidisciplinary Design Optimization of Complex Structures Under Uncertainty caters to a diverse audience: Engineers specializing in multidisciplinary design optimization are given the tools to master uncertainty management, and researchers in related fields will gain important theoretical insights and practical guidance in uncertainty analysis. Additionally, scholars and educators can utilize the book as a comprehensive resource for advanced courses, enabling students to grasp the latest UBMDO applications. Decision makers and managers handling complex systems can extract methods from the book, facilitating improved risk assessment, and strategic development through uncertainty-based optimization. From basic theory to advanced applications, this helps readers achieve more efficient and reliable design optimization in complex systems through rich case studies and practical technical guidance, presenting the fundamental theories and methods of Uncertainty-Based Multidisciplinary Design and Optimization. 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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Da: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller
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EUR 78,60
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Hardcover. Condizione: new. Hardcover. This Reprint contains all of the articles that were accepted and published in the Special Issue of Mathematics titled "Modeling and Optimization of Complex Engineering Systems under Uncertainties". It offers a comprehensive overview of the current state of the art in reliability engineering… and applied mathematics. The research highlights a fundamental transition in engineering design and control, moving away from static safety factors toward dynamic, probabilistic, and data-driven frameworks. We have observed that hybrid optimization algorithms, such as the coupled Simulated Annealing and Particle Swarm Optimization, offer superior efficiency in navigating high-dimensional design spaces. We have seen that Scientific Machine Learning can be made robust to uncertainty through Bayesian inference, ensuring that soft sensors and control models remain trustworthy in critical applications. Furthermore, the successful application of these methods to diverse fields, including tunnel engineering, wind energy, structural health monitoring, and construction safety, confirms the universal relevance of uncertainty quantification. We hope that the methodologies and findings presented in this volume will serve as a foundation for future inquiries and inspire researchers to further explore the intricate dynamics of complex engineering systems. 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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Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 69,49
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Hardcover. Condizione: new. Hardcover. This Reprint contains all of the articles that were accepted and published in the Special Issue of Mathematics titled "Modeling and Optimization of Complex Engineering Systems under Uncertainties". It offers a comprehensive overview of the current state of the art in reliability engineering… and applied mathematics. The research highlights a fundamental transition in engineering design and control, moving away from static safety factors toward dynamic, probabilistic, and data-driven frameworks. We have observed that hybrid optimization algorithms, such as the coupled Simulated Annealing and Particle Swarm Optimization, offer superior efficiency in navigating high-dimensional design spaces. We have seen that Scientific Machine Learning can be made robust to uncertainty through Bayesian inference, ensuring that soft sensors and control models remain trustworthy in critical applications. Furthermore, the successful application of these methods to diverse fields, including tunnel engineering, wind energy, structural health monitoring, and construction safety, confirms the universal relevance of uncertainty quantification. We hope that the methodologies and findings presented in this volume will serve as a foundation for future inquiries and inspire researchers to further explore the intricate dynamics of complex engineering systems. 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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- Print on Demand
Da: CitiRetail, Stevenage, Regno UnitoCitiRetail
Contatta il venditoreVenditore con 5 stelleCondizione: Nuovo
EUR 75,54
EUR 43,43 spedizioneSpedito da Regno Unito a U.S.A.Quantità: 1 disponibili
Paperback. Condizione: new. Paperback. In the realm of engineering structures design, the inevitability of uncertainties poses a significant challenge. Uncertainty-Based Multidisciplinary Design and Optimization (UBMDO) stands out for its dual ability to precisely quantify the impact of uncertain variables and harness the potent…ial of multidisciplinary design and optimization, thereby attracting considerable attention. From basic theory to advanced applications, this book helps readers achieve more efficient and reliable design optimization in complex systems through rich case studies and practical technical guidance.The book systematically expounds the fundamental theories and methods of UBMDO, encompassing crucial techniques such as uncertainty modeling, sensitivity analysis, approximate modeling, and uncertainty-based optimization. It also introduces various uncertainty analysis methods, such as stochastic, non-probabilistic, and hybrid approaches, aiding readers in comprehending and managing uncertainty within systems. Through diverse practical engineering cases in fields like machinery, aerospace, and energy, it illustrates the specific application and implementation process of the UBMDO method. Rich graphics, algorithms, and simulation results augment the practicality and applicability of the theoretical knowledge. Furthermore, it explores in depth the future development trends and challenges of UBMDO, sparking innovative thinking and research interests among readers in this field.Multidisciplinary Design Optimization of Complex Structures Under Uncertainty caters to a diverse audience: Engineers specializing in multidisciplinary design optimization are given the tools to master uncertainty management, and researchers in related fields will gain important theoretical insights and practical guidance in uncertainty analysis. Additionally, scholars and educators can utilize the book as a comprehensive resource for advanced courses, enabling students to grasp the latest UBMDO applications. Decision makers and managers handling complex systems can extract methods from the book, facilitating improved risk assessment, and strategic development through uncertainty-based optimization. From basic theory to advanced applications, this helps readers achieve more efficient and reliable design optimization in complex systems through rich case studies and practical technical guidance, presenting the fundamental theories and methods of Uncertainty-Based Multidisciplinary Design and Optimization. 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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- Print on Demand
Da: Majestic Books, Hounslow, Regno UnitoMajestic Books
Contatta il venditoreVenditore con 4 stelleCondizione: Nuovo
EUR 113,88
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Condizione: New. Print on Demand.