In today's complex operational environments, leveraging advanced decision-making tools becomes imperative, particularly in uncertain scenarios. This book deepens the nuances of employing state-of-the-art decision-...
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ISBN:
(数字)9783031517198
ISBN:
(纸本)9783031517181;9783031517211
In today's complex operational environments, leveraging advanced decision-making tools becomes imperative, particularly in uncertain scenarios. This book deepens the nuances of employing state-of-the-art decision-making methodologies within various industrial sectors for optimal project and operations management. The essence of integrating these advanced tools is to equip professionals with pivotal insights for cost-effective management and to strategize against potential operational shortcomings. Furthermore, the methodologies elucidated provide a robust foundation for crafting informed, risk-centric strategies that uphold the integrity of operations across diverse application domains. Readers will discover a rich tapestry of methodologies tailored for engineers and analysts. Deeply rooted in mathematical modeling, these approaches are complemented by human judgment and participation. Fundamental attributes of these methods include the evaluation of alternatives, benchmarking againstcriteria, assigning scores based on varying requirements, and assigning weights to denote the significance of individual criteria vis-à-vis others. The book embarks on a structured journey, commencing with a comprehensive review of evolving decision-making methodologies in project and operations management, enriched by metadata analysis. Subsequent chapters are meticulously organized, each spotlighting a distinct approach. Topics span foundational concepts in decision-making, the nuances of performance metrics in the digital age, and the implications of emerging technologies on operations management. Targeted towards professionals and researchers immersed in project and operations management, this work will also immensely benefit postgraduate and undergraduate students in related fields. Moreover, its relevance extends to professionals across diverse sectors, from oil and gas, marine and offshore, and renewable energies to chemical complexes, manufacturing, and healthcare systems.
This book suggests the development of single and multi-layer fractional-order neural networks that incorporate fractional-order activation functions derived using fractional-order derivatives. Activation functions are...
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ISBN:
(数字)9783031880919
ISBN:
(纸本)9783031880902;9783031880933
This book suggests the development of single and multi-layer fractional-order neural networks that incorporate fractional-order activation functions derived using fractional-order derivatives. Activation functions are essential in neural networks as they introduce nonlinearity, enabling the models to learn complex patterns in data. However, traditional activation functions have limitations such as non-differentiability, vanishing gradient problems, and inactive neurons at negative inputs, which can affect the performance of neural networks, especially for tasks involving intricate nonlinear dynamics. To address these issues, fractional-order derivatives from fractional calculus have been proposed. These derivatives can model complex systems with non-local or non-Markovian behavior. The aim is to improve wind power prediction accuracy using datasets from the Texas wind turbine and Jeju Island wind farm under various scenarios. The book explores the advantages of fractional-order activation functions in terms of robustness, faster convergence, and greater flexibility in hyper-parameter tuning. It includes a comparative analysis of single and multi-layer fractional-order neural networks versus conventional neural networks, assessing their performance based on metrics such as mean square error and coefficient of determination. The impact of using machine learning models to impute missing data on the performance of networks is also discussed. This book demonstrates the potential of fractional-order activation functions to enhance neural network models, particularly in predicting chaotic time series. The findings suggest that fractional-order activation functions can significantly improve accuracy and performance, emphasizing the importance of advancing activation function design in neural network analysis. Additionally, the book is a valuable teaching and learning resource for undergraduate and postgraduate students conducting research in this field.
This book provides a series of systematic theoretical results and numerical solution algorithms for dynamic optimization problems of switched systems within infinite-dimensional inequality path constraints. Dynamic op...
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ISBN:
(数字)9783031234286
ISBN:
(纸本)9783031234279;9783031234309
This book provides a series of systematic theoretical results and numerical solution algorithms for dynamic optimization problems of switched systems within infinite-dimensional inequality path constraints. Dynamic optimization of path-constrained switched systems is a challenging task due to the complexity from seeking the best combinatorial optimization among the system input, switch times and switching sequences. Meanwhile, to ensure safety and guarantee product quality, path constraints are required to be rigorously satisfied (i.e., at an infinite number of time points) within a finite number of iterations.;Several novel methodologies are presented by using dynamic optimization and semi-infinite programming techniques. The core advantages of our new approaches lie in two folds: i) The system input, switch times and the switching sequence can be optimized simultaneously. ii) The proposed algorithms terminate within finite iterations while coming witha certification of feasibility for the path constraints.;In this book, first, we provide brief surveys on dynamic optimization of path-constrained systems and switched systems. For switched systems with a fixed switching sequence, we propose a bi-level algorithm, in which the input is optimized at the inner level, and the switch times are updated at the outer level by using the gradient information of the optimal value function calculated at the optimal input. We then propose an efficient single-level algorithm by optimizing the input and switch times simultaneously, which greatly reduces the number of nonlinear programs and the computational burden. For switched systems with free switching sequences, we propose a solution framework for dynamic optimization of path-constrained switched systems by employing the variant 2 of generalized Benders decomposition technique. In this framework, we adopt two different system formulations in the primal and master problem construction and explicitly characterize the switching seq
This book gathers cutting-edge research and best practices relating to occupational risk and safetymanagement, healthcare, and ergonomics. It covers strategies for different industries, such as construction,chemical, ...
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ISBN:
(数字)9783031821660
ISBN:
(纸本)9783031821653;9783031821684
This book gathers cutting-edge research and best practices relating to occupational risk and safety
management, healthcare, and ergonomics. It covers strategies for different industries, such as construction,
chemical, and healthcare. It emphasizes challenges posed by automation, discusses solutions offered by
technologies, and reports on case studies carried out in different countries. Chapters are based on selected
contributions to the 21st International Symposium on Occupational Safety and Hygiene (SHO 2024), held on
July 4-5, 2024, in Porto, Portugal. By reporting on different perspectives, such as the ones from managers,
employees, and OSH professionals, and covering timely issues, such as implications of telework, issues related
to gender inequality and applications of machine learning techniques in occupational health, this book offers
extensive information and a source of inspiration to OSH researchers, practitioners, and organizations
operating in both local and global contexts. This is the first volume of a 2-volume set.
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