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Data Science: Theory, Algorithms, and Applications, Verma Gyanendra K., Soni Badal, Bourennane Salah


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Цена: 158380.00T
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Автор: Verma Gyanendra K., Soni Badal, Bourennane Salah
Название:  Data Science: Theory, Algorithms, and Applications
ISBN: 9789811616808
Издательство: Springer
Классификация:


ISBN-10: 9811616809
Обложка/Формат: Hardcover
Страницы: 437
Вес: 0.91 кг.
Дата издания: 08.09.2021
Язык: English
Размер: 23.88 x 20.07 x 2.54 cm
Ссылка на Издательство: Link
Поставляется из: Германии
Описание: By the end of the book, the readers will have an understanding of different deep learning approaches, models, pre-trained models, and familiarity with the implementation of various deep learning algorithms using various frameworks and libraries.

Machine Learning Guide for Oil and Gas Using Python: A Step-By-Step Breakdown with Data, Algorithms, Codes, and Applications

Автор: Belyadi Hoss, Haghighat Alireza
Название: Machine Learning Guide for Oil and Gas Using Python: A Step-By-Step Breakdown with Data, Algorithms, Codes, and Applications
ISBN: 0128219297 ISBN-13(EAN): 9780128219294
Издательство: Elsevier Science
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Цена: 129130.00 T
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Описание:

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges.


Evolutionary Data Clustering: Algorithms and Applications

Автор: Aljarah Ibrahim, Faris Hossam, Mirjalili Seyedali
Название: Evolutionary Data Clustering: Algorithms and Applications
ISBN: 9813341939 ISBN-13(EAN): 9789813341937
Издательство: Springer
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Цена: 167700.00 T
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Описание: It features a range of proven and recent nature-inspired algorithms used to data clustering, including particle swarm optimization, ant colony optimization, grey wolf optimizer, salp swarm algorithm, multi-verse optimizer, Harris hawks optimization, beta-hill climbing optimization.

Grammatical Inference: Algorithms and Applications

Автор: Alexander Clark; Fran?ois Coste; Laurent Miclet
Название: Grammatical Inference: Algorithms and Applications
ISBN: 3540880089 ISBN-13(EAN): 9783540880080
Издательство: Springer
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Цена: 65210.00 T
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Описание: Constitutes the refereed proceedings of the 9th International Colloquium on Grammatical Inference, ICGI 2008, held in Saint-Malo, France, in September 2008. This title also includes papers on topics ranging from theoretical results of learning algorithms to innovative applications of grammatical inference.

Knowledge Acquisition: Approaches, Algorithms and Applications

Автор: Debbie Richards; Byeong-Ho Kang
Название: Knowledge Acquisition: Approaches, Algorithms and Applications
ISBN: 3642017142 ISBN-13(EAN): 9783642017148
Издательство: Springer
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Цена: 65210.00 T
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Описание: This book constitutes the thoroughly refereed post-workshop proceedings of the 2008 Pacific Rim Knowledge Acquisition Workshop, PKAW 2008, held in Hanoi, Vietnam, in December 2008 as part of 10th Pacific Rim International Conference on Artificial Intelligence, PRICAI 2008.

Emotional Cognitive Neural Algorithms with Engineering Applications

Автор: Leonid Perlovsky; Ross Deming; Roman Ilin
Название: Emotional Cognitive Neural Algorithms with Engineering Applications
ISBN: 3642269389 ISBN-13(EAN): 9783642269387
Издательство: Springer
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Цена: 121890.00 T
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Описание: Dynamic logic (DL) recently had a highest impact on the development in several areas of modeling and algorithm design. Emerging areas include cognitive, emotional, intelligent systems, data mining, modeling of the mind, higher cognitive functions, evolution of languages and other.

Advances and Applications of Optimised Algorithms in Image Processing

Автор: Diego Oliva; Erik Cuevas
Название: Advances and Applications of Optimised Algorithms in Image Processing
ISBN: 3319485490 ISBN-13(EAN): 9783319485492
Издательство: Springer
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Цена: 111790.00 T
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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.

Industrial Applications of Evolutionary Algorithms

Автор: Ernesto Sanchez; Giovanni Squillero; Alberto Tonda
Название: Industrial Applications of Evolutionary Algorithms
ISBN: 364244346X ISBN-13(EAN): 9783642443466
Издательство: Springer
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Цена: 104480.00 T
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Описание: Ideal as a reference both for experienced users and novices, this publication combines a thorough introduction to evolutionary computation with details of its application to real-world problems and advice on tackling a wealth of issues in its implementation.

Extreme Learning Machines 2013: Algorithms and Applications

Автор: Fuchen Sun; Kar-Ann Toh; Manuel Grana Romay; Kezhi
Название: Extreme Learning Machines 2013: Algorithms and Applications
ISBN: 331904740X ISBN-13(EAN): 9783319047409
Издательство: Springer
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Цена: 130610.00 T
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Описание: An extreme learning machine (ELM) is a single layer feed-forward neural network alike learning system, whose connections from the input layer to the hidden layer are randomly generated, while the connections from the hidden layer to the output layer are learned through linear learning methods.

Recent Algorithms and Applications in Swarm Intelligence Research

Автор: Yuhui Shi
Название: Recent Algorithms and Applications in Swarm Intelligence Research
ISBN: 1466624795 ISBN-13(EAN): 9781466624795
Издательство: Mare Nostrum (Eurospan)
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Цена: 189420.00 T
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Описание: Advances in the nature-inspired swarm intelligence algorithms continue to be useful in solving complicated problems in nonlinear, non-differentiable, and un-continuous functions, as well as being applied to solve real-world applications. This title highlights the current research on swarm intelligence algorithms and its applications.

Artificial Intelligence In Highway Location And Alignment Optimization: Applications Of Genetic Algorithms In Searching, Evaluating, And Optimizing Highway Location And Alignments

Автор: Kang Min-wook, Schonfeld Paul
Название: Artificial Intelligence In Highway Location And Alignment Optimization: Applications Of Genetic Algorithms In Searching, Evaluating, And Optimizing Highway Location And Alignments
ISBN: 9813272805 ISBN-13(EAN): 9789813272804
Издательство: World Scientific Publishing
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Цена: 95040.00 T
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Описание: This monograph provides a comprehensive overview of methods for searching, evaluating, and optimizing highway location and alignments using genetic algorithms (GAs), a powerful Artificial Intelligence (AI) technique. It presents a two-level programming structure to deal with the effects of varying highway location on traffic level changes in surrounding road networks within the highway location search and alignment optimization process. In addition, the proposed method evaluates environmental impacts as well as all relevant highway costs associated with its construction, operation, and maintenance. The monograph first covers various search methods, relevant cost functions, constraints, computational efficiency, and solution quality issues arising from optimizing the highway alignment optimization (HAO) problem. It then focuses on applications of a special-purpose GA in the HAO problem where numerous highway alignments are generated and evaluated, and finally the best ones are selected based on costs, traffic impacts, safety, energy, and environmental considerations. A review of other promising optimization methods for the HAO problem is also provided in this monograph.

Machine Learning Algorithms for Industrial Applications

Автор: Das, S.K., Das, S.P., Dey, N., Hassanien, A.-E.
Название: Machine Learning Algorithms for Industrial Applications
ISBN: 3030506401 ISBN-13(EAN): 9783030506407
Издательство: Springer
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Цена: 139750.00 T
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Описание: This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics.

Machine Learning Applications: Emerging Trends

Автор: Rik Das, Siddhartha Bhattacharyya, Sudarshan Nandy
Название: Machine Learning Applications: Emerging Trends
ISBN: 3110608537 ISBN-13(EAN): 9783110608533
Издательство: Walter de Gruyter
Цена: 123910.00 T
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Описание:

The publication is attempted to address emerging trends in machine learning applications. Recent trends in information identification have identified huge scope in applying machine learning techniques for gaining meaningful insights. Random growth of unstructured data poses new research challenges to handle this huge source of information. Efficient designing of machine learning techniques is the need of the hour. Recent literature in machine learning has emphasized on single technique of information identification. Huge scope exists in developing hybrid machine learning models with reduced computational complexity for enhanced accuracy of information identification. This book will focus on techniques to reduce feature dimension for designing light weight techniques for real time identification and decision fusion. Key Findings of the book will be the use of machine learning in daily lives and the applications of it to improve livelihood. However, it will not be able to cover the entire domain in machine learning in its limited scope. This book is going to benefit the research scholars, entrepreneurs and interdisciplinary approaches to find new ways of applications in machine learning and thus will have novel research contributions. The lightweight techniques can be well used in real time which will add value to practice.



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