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Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems, Houssein


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Цена: 19564.00р.
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Автор: Houssein
Название:  Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
ISBN: 9783030990787
Издательство: Springer
Классификация:

ISBN-10: 3030990788
Обложка/Формат: Hardback
Страницы: 497
Вес: 0.93 кг.
Дата издания: 19.06.2022
Серия: Studies in Computational Intelligence
Язык: English
Издание: 1st ed. 2022
Иллюстрации: 20 tables, color; 183 illustrations, color; 44 illustrations, black and white; ix, 497 p. 227 illus., 183 illus. in color.
Размер: 235 x 155
Читательская аудитория: Professional & vocational
Основная тема: Engineering
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.
Дополнительное описание: Combined Optimization Algorithms for Incorporating DG in Distribution Systems.- Intelligent computational models for cancer diagnosis: A Comprehensive Review.- Elitist-Ant System metaheuristic for ITC 2021- Sports Timetabling.- Swarm intelligence algorith



Data-driven science and engineering

Автор: Brunton, Steven L. (university Of Washington) Kutz
Название: Data-driven science and engineering
ISBN: 1009098489 ISBN-13(EAN): 9781009098489
Издательство: Cambridge Academ
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Цена: 7918.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Data-driven discovery is revolutionizing how we model, predict, and control complex systems. This text integrates emerging machine learning and data science methods for engineering and science communities. Now with Python and MATLAB (R), new chapters on reinforcement learning and physics-informed machine learning, and supplementary videos and code.

Simple heuristics that make us smart

Автор: Gigerenzer, Gerd (director, Center For Adaptive Be
Название: Simple heuristics that make us smart
ISBN: 0195143817 ISBN-13(EAN): 9780195143812
Издательство: Oxford Academ
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Цена: 8712.00 р.
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Описание: This work provides a psychologically plausible notion of rationality that is based on heuristics -- simple rules for making decisions using realistic mental resources. It looks at when and how such simple heuristics work, compares decisions based on single and multiple reasons, and describes benefits in situations of having only limited knowledge.

Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities

Автор: Hatti
Название: Artificial Intelligence and Heuristics for Smart Energy Efficiency in Smart Cities
ISBN: 3030920402 ISBN-13(EAN): 9783030920401
Издательство: Springer
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Цена: 32142.00 р.
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Описание: This book emphasizes the role of micro-grid systems and connected networks for the strategic storage of energy through the use of information and communication techniques, big data, the cloud, and meta-heuristics to support the greed for artificial intelligence techniques in data and the implementation of global strategies to meet the challenges of the city in the broad sense. The intelligent management of renewable energy in the context of the energy transition requires the use of techniques and tools based on artificial intelligence (AI) to overcome the challenges of the intermittence of resources and the cost of energy. The advent of the smart city makes an increased call for the integration of artificial intelligence and heuristics to meet the challenge of the increasing migration of populations to the city, in order to ensure food, energy, and environmental security of the citizen of the city and his well-being. This book is intended for policymakers, academics, practitioners, and students. Several real cases are exposed throughout the book to illustrate the concepts and methods of the networks and systems presented. This book proposes the development of new technological innovations—mainly ICT—the concept of “Smart City” appears as a means of achieving more efficient and sustainable cities. The overall goal of the book is to develop a comprehensive framework to help public and private stakeholders make informed decisions on smart city investment strategies and develop skills for assessment and prioritization, including resolution of difficulties with deployment and reproducibility.

Hyper-Heuristics: Theory and Applications

Автор: Nelishia Pillay; Rong Qu
Название: Hyper-Heuristics: Theory and Applications
ISBN: 3319965131 ISBN-13(EAN): 9783319965130
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This introduction to the field of hyper-heuristics presents the required foundations and tools and illustrates some of their applications. The authors organized the 13 chapters into three parts. The first, hyper-heuristic fundamentals and theory, provides an overview of selection constructive, selection perturbative, generation constructive and generation perturbative hyper-heuristics, and then a formal definition of hyper-heuristics. The chapters in the second part of the book examine applications of hyper-heuristics in vehicle routing, nurse rostering, packing and examination timetabling. The third part of the book presents advanced topics and then a summary of the field and future research directions. Finally the appendices offer details of the HyFlex framework and the EvoHyp toolkit, and then the definition, problem model and constraints for the most tested combinatorial optimization problems. The book will be of value to graduate students, researchers, and practitioners.

Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science

Автор: Jin Yaochu, Wang Handing, Sun Chaoli
Название: Data-Driven Evolutionary Optimization: Integrating Evolutionary Computation, Machine Learning and Data Science
ISBN: 3030746399 ISBN-13(EAN): 9783030746391
Издательство: Springer
Цена: 22359.00 р.
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Описание: This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms.

Data-Driven Evolutionary Optimization

Автор: Jin
Название: Data-Driven Evolutionary Optimization
ISBN: 3030746429 ISBN-13(EAN): 9783030746421
Издательство: Springer
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Цена: 22359.00 р.
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Описание: This is followed by a presentation of a variety of data-driven single- and multi-objective optimization algorithms that seamlessly integrate modern machine learning such as deep learning and transfer learning with evolutionary and swarm optimization algorithms.

Beyond the Worst-Case Analysis of Algorithms

Автор: Tim Roughgarden
Название: Beyond the Worst-Case Analysis of Algorithms
ISBN: 1108494315 ISBN-13(EAN): 9781108494311
Издательство: Cambridge Academ
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Цена: 9187.00 р.
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Описание: Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case analysis. The book introduces exciting new methods for assessing algorithm performance.

Meta-Heuristics

Автор: Stefan Vo?; Silvano Martello; Ibrahim H. Osman; Ca
Название: Meta-Heuristics
ISBN: 1461376467 ISBN-13(EAN): 9781461376460
Издательство: Springer
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Цена: 27950.00 р.
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Описание: Meta-Heuristics: Advances and Trends in Local Search Paradigms for Optimizations comprises a carefully refereed selection of extended versions of the best papers presented at the Second Meta-Heuristics Conference (MIC 97).

Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance

Автор: Pandian Vasant
Название: Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance
ISBN: 1466620862 ISBN-13(EAN): 9781466620865
Издательство: Mare Nostrum (Eurospan)
Рейтинг:
Цена: 28413.00 р.
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Описание: Meta-Heuristics Optimization Algorithms in Engineering, Business, Economics, and Finance explores the emerging study of meta-heuristics optimization algorithms and methods and their role in innovated real world practical applications. This book is a collection of research on the areas of meta-heuristics optimization algorithms in engineering, business, economics, and finance, and aims to be a comprehensive reference for decision makers, managers, engineers, researchers, scientists, financiers, and economists as well as industrialists.

Heuristics for Optimization and Learning

Автор: Yalaoui Farouk, Amodeo Lionel, Talbi El-Ghazali
Название: Heuristics for Optimization and Learning
ISBN: 3030589323 ISBN-13(EAN): 9783030589325
Издательство: Springer
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Цена: 23757.00 р.
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Описание: This book is a new contribution aiming to give some last research findings in the field of optimization and computing. The challenge with this work is to gather the main contribution in three fields, optimization technique for production decision, general development for optimization and computing method and wider spread applications.

Bioinspired Heuristics for Optimization

Автор: El-Ghazali Talbi; Amir Nakib
Название: Bioinspired Heuristics for Optimization
ISBN: 3030069788 ISBN-13(EAN): 9783030069780
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
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Описание: This book presents recent research on bioinspired heuristics for optimization. Learning- based and black-box optimization exhibit some properties of intrinsic parallelization, and can be used for various optimizations problems. Featuring the most relevant work presented at the 6th International Conference on Metaheuristics and Nature Inspired Computing, held at Marrakech (Morocco) from 27th to 31st October 2016, the book presents solutions, methods, algorithms, case studies, and software. It is a valuable resource for research academics and industrial practitioners.

Bioinspired Heuristics for Optimization

Автор: Talbi
Название: Bioinspired Heuristics for Optimization
ISBN: 3319951033 ISBN-13(EAN): 9783319951034
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents recent research on bioinspired heuristics for optimization. Featuring the most relevant work presented at the 6th International Conference on Metaheuristics and Nature Inspired Computing, held at Marrakech (Morocco) from 27th to 31st October 2016, the book presents solutions, methods, algorithms, case studies, and software.


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