Asaf hajiyev (133 resultados)

Condición: New. Jiuping Xu is Distinguished Professor of Sichuan University, P.R. China, and Editor-in-Chief of International Journal of Management Science and Engineering Management. His research interests include emergency management, urban resilience, d.

Taschenbuch. Condición: Neu. Neuware - This book offers a comprehensive exploration of the latest advancements in sustainable and resilient supply chain management. The chapters in this volume present a diverse range of topics, including innovative strategies for optimizing sustainable food supply chains through data envelopment analysis, dynamic multi-modal perspectives on global supply chain network configuration, and robust data-driven optimization techniques for designing sustainable cold supply chains for livestock and perishable goods. Other chapters delve into key areas such as optimal pricing and production lot size strategies for sustainable inventory models, carbon-sensitive transport solutions for deteriorating supply chains, and trade credit policies in growing product supply chains.Additionally, the book addresses the complexities of inventory management, purchasing, and cutting policies for imperfect and perishable raw materials, the influence of supply chain finance and trade digitization on financial stability, and the development of heuristic master planning algorithms that prioritize fairness and flexibility. Further studies examine adaptive product changeover policies, a PDCA-based approach to evaluating green supply chain performance, and robust multi-criteria decision analysis techniques for selecting transportation service providers in the face of uncertainty. By offering insights into both theoretical and practical aspects, this book provides a valuable resource for researchers, practitioners, and policymakers looking to navigate the evolving landscape of sustainable supply chains. This book will be valuable to students, researchers and policymakers in the fields of supply chain management, sustainable logistics and operations research.The chapters in this book were originally published in International Journal of Management Science and Engineering Management.…

Condición: As New. Unread book in perfect condition.

Condición: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New.

Condición: New.

Condición: As New. Unread book in perfect condition.

Condición: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Condición: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Condición: New. A brand new book in pristine condition. Showing zero signs of shelf wear, creases, or damage.

Hardback. Condición: New. Queuing theory methods are employed in managing traffic flows, shipping facilities, communication systems, vertical transportation, and others. The study of such systems is outside the framework of the methods of classical queuing theory; thus, new methodologies, such as systems with moving servers, have evolved. These systems are different and have complicated structures, but they have one common ideology, i.e. systems with moving servers. The book is dedicated to constructing and investigating mathematical models of queueing systems with moving servers.It is meant for researchers who are working in the application of mathematical methods in various fields (traffic, communication systems, and others), mathematicians in the field of queueing systems, also researchers who are interested in the construction and investigation of mathematical models of queueing systems with moving servers. The theoretical results are demonstrated on numerical examples.…

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Condición: New.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this book, a novel high-dimensional linear andnonlinear regression model is introduced to address, in part, the challenges of evaluating the stability and confidence of large-scale models' interpretability. The book begins by reviewing foundational concepts in regression analysis, and discussing the current state and challenges of AI interpretability. Through an in-depth exploration of regression models, the core principles of data-driven linear regression are explained. To enhance the explanatory power of regression models, variable-parameter regression models are further investigated and extended to variable-parameter nonlinear regression models. To handle complex relationships, the Gauss-Newton iterative method is incorporated, ensuring the stability of high-dimensional nonlinear regression. The Confidence Interval-based Credibility Evaluation (CICE) framework combines statistical indicators such as interval width, center deviation, and accuracy into a single score to assess the stability and reliability of explanations, validated through case studies in engineering, finance, and time series prediction. Overall, the book presents a coherent framework for interpretable AI, integrating regression modeling, confidence region construction, and credibility evaluation to enhance interpretability and statistical accountability, fostering more trustworthy AI systems. Chapter 1 introduces the fundamental concepts and theoretical developments of both regression analysis and AI explainability, highlighting their interconnections. Chapter 2 reviews essential probability theory and mathematical statistics, covering random variables, measure spaces, probability distributions, parameter estimation (including least squares and maximum likelihood methods), and asymptotic theory, which serve as the foundation for analyzing model consistency and convergence. Chapter 3 focuses on the effects of correlated errors in linear regression, establishing parameter convergence conditions to ensure the consistency and asymptotic normality of covariance estimators. Chapter 4 introduces variable-parameter regression models and systematically studies M-estimators and generalized regression models within the framework of robust statistics. By addressing non-normal errors and outliers, these methods improve model adaptability. The chapter also establishes the robustness of the generalized regression model through theoretical analysis of covariance estimation. Chapter 5 introduces the Confidence Interval-based Credibility Evaluation (CICE) framework, which integrates multiple statistical indicators into a unified score to assess the stability and reliability of model explanations. Through real-world case studies in engineering, finance, and time series prediction, the effectiveness of CICE in detecting unstable interpretations and enhancing model transparency is demonstrated.…

Hardcover. Condición: Brand New. 256 pages. 9.18x6.12x9.21 inches. In Stock.

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Taschenbuch. Condición: Neu. Proceedings of the Fourteenth International Conference on Management Science and Engineering Management | Volume 2 | Jiuping Xu (u. a.) | Taschenbuch | Advances in Intelligent Systems and Computing | xvi | Englisch | 2020 | Springer | EAN 9783030498887 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.…

Condición: New.

Condición: New. Jiuping Xu is Distinguished Professor of Sichuan University, P.R. China, and Editor-in-Chief of International Journal of Management Science and Engineering Management. His research interests include emergency management, urban resilience, d.

Condición: As New. Unread book in perfect condition.

Condición: New.

Condición: New. In English.

Condición: New. In English.