Автор: Huyen Pham Название: Continuous-time Stochastic Control and Optimization with Financial Applications ISBN: 3540894993 ISBN-13(EAN): 9783540894995 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This text provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations and martingale duality methods.
Автор: Jude Hemanth; Valentina Emilia Balas Название: Biologically Rationalized Computing Techniques For Image Processing Applications ISBN: 3319613154 ISBN-13(EAN): 9783319613154 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces readers to innovative bio-inspired computing techniques for image processing applications. It demonstrates how a significant drawback of image processing - not providing the simultaneous benefits of high accuracy and less complexity - can be overcome, proposing bio-inspired methodologies to help do so.
Автор: Salazar Niceto Название: Concepts and Applications of Image Processing Techniques ISBN: 1632401150 ISBN-13(EAN): 9781632401151 Издательство: Неизвестно Цена: 101870.00 T Наличие на складе: Есть у поставщика Поставка под заказ.
This book introduces readers to innovative bio-inspired computing techniques for image processing applications. It demonstrates how a significant drawback of image processing – not providing the simultaneous benefits of high accuracy and less complexity – can be overcome, proposing bio-inspired methodologies to help do so.
Besides computing techniques, the book also sheds light on the various application areas related to image processing, and weighs the pros and cons of specific methodologies. Even though several such methodologies are available, most of them do not provide the simultaneous benefits of high accuracy and less complexity, which explains their low usage in connection with practical imaging applications, such as the medical scenario. Lastly, the book illustrates the methodologies in detail, making it suitable for newcomers to the field and advanced researchers alike.
Автор: Xin-She Yang Название: Bio-Inspired Computation and Applications in Image Processing ISBN: 0128045361 ISBN-13(EAN): 9780128045367 Издательство: Elsevier Science Рейтинг: Цена: 116780.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Bio-Inspired Computation and Applications in Image Processing summarizes the latest developments in bio-inspired computation in image processing, focusing on nature-inspired algorithms that are linked with deep learning, such as ant colony optimization, particle swarm optimization, and bat and firefly algorithms that have recently emerged in the field.
In addition to documenting state-of-the-art developments, this book also discusses future research trends in bio-inspired computation, helping researchers establish new research avenues to pursue.
Автор: Soliman Abdel-Hady Soliman; Abdel-Aal Hassan Manta Название: Modern Optimization Techniques with Applications in Electric Power Systems ISBN: 148998979X ISBN-13(EAN): 9781489989796 Издательство: Springer Рейтинг: Цена: 144410.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Presenting ways of using AI optimization techniques to operate and control electric power systems, this book is full of practical applications and examples and features, among other methods, functional analysis, simulated annealing and Tabu-search.
Автор: Yang Название: Optimization Techniques and Applications with Examples ISBN: 1119490545 ISBN-13(EAN): 9781119490548 Издательство: Wiley Рейтинг: Цена: 109770.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
A guide to modern optimization applications and techniques in newly emerging areas spanning optimization, data science, machine intelligence, engineering, and computer sciences
Optimization Techniques and Applications with Examples introduces the fundamentals of all the commonly used techniques in optimization that encompass the broadness and diversity of the methods (traditional and new) and algorithms. The author--a noted expert in the field--covers a wide range of topics including mathematical foundations, optimization formulation, optimality conditions, algorithmic complexity, linear programming, convex optimization, and integer programming. In addition, the book discusses artificial neural network, clustering and classifications, constraint-handling, queueing theory, support vector machine and multi-objective optimization, evolutionary computation, nature-inspired algorithms and many other topics.
Designed as a practical resource, all topics are explained in detail with step-by-step examples to show how each method works. The book's exercises test the acquired knowledge that can be potentially applied to real problem solving. By taking an informal approach to the subject, the author helps readers to rapidly acquire the basic knowledge in optimization, operational research, and applied data mining. This important resource:
Offers an accessible and state-of-the-art introduction to the main optimization techniques
Contains both traditional optimization techniques and the most current algorithms and swarm intelligence-based techniques
Presents a balance of theory, algorithms, and implementation
Includes more than 100 worked examples with step-by-step explanations
Written for upper undergraduates and graduates in a standard course on optimization, operations research and data mining, Optimization Techniques and Applications with Examples is a highly accessible guide to understanding the fundamentals of all the commonly used techniques in optimization.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Pandian Vasant Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 179981193X ISBN-13(EAN): 9781799811930 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 180180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Автор: J. Joshua Thomas, Pinar Karagoz, B. Bazeer Ahamed, Название: Deep Learning Techniques and Optimization Strategies in Big Data Analytics ISBN: 1799811921 ISBN-13(EAN): 9781799811923 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 239310.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there's a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Автор: Tamas Terlaky and Miguel F. Anjos Название: Advances and Trends in Optimization with Engineering Applications ISBN: 1611974674 ISBN-13(EAN): 9781611974676 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 101640.00 T Наличие на складе: Невозможна поставка. Описание: Optimization is of critical importance in engineering. This overview of state-of-the-art optimization techniques reviews 10 major areas of optimization and related engineering applications. It provides a solid foundation for engineers and mathematical optimizers alike who want to understand not only the importance of optimization methods to engineering but also the capabilities of current methods.
Автор: Diego Oliva; Erik Cuevas Название: Advances and Applications of Optimised Algorithms in Image Processing ISBN: 3319485490 ISBN-13(EAN): 9783319485492 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book presents a study of the use of optimization algorithms in complex image processing problems. The problems selected explore areas ranging from the theory of image segmentation to the detection of complex objects in medical images. Furthermore, the concepts of machine learning and optimization are analyzed to provide an overview of the application of these tools in image processing. The material has been compiled from a teaching perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics, and can be used for courses on Artificial Intelligence, Advanced Image Processing, Computational Intelligence, etc. Likewise, the material can be useful for research from the evolutionary computation, artificial intelligence and image processing communities.
In the field of image processing, many applications require real-time execution, particularly those in the domains of medicine, robotics and transmission, to name but a few. Recent technological developments have allowed for the integration of more complex algorithms with large data volume into embedded systems, in turn producing a series of new sophisticated electronic architectures at affordable prices. This book performs an in-depth survey on this topic. It is primarily written for those who are familiar with the basics of image processing and want to implement the target processing design using different electronic platforms for computing acceleration. The authors present techniques and approaches, step by step, through illustrative examples. This book is also suitable for electronics/embedded systems engineers who want to consider image processing applications as sufficient imaging algorithm details are given to facilitate their understanding.
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