Water and Energy Management in India: Artificial Neural Networks and Multi-Criteria Decision Making Approaches, Majumder Mrinmoy, Kale Ganesh D.
Автор: Chi-Bin Cheng; Hsu-Shih Shih; E. Stanley Lee Название: Fuzzy and Multi-Level Decision Making: Soft Computing Approaches ISBN: 3319925245 ISBN-13(EAN): 9783319925240 Издательство: Springer Рейтинг: Цена: 93160.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.
Автор: Majumder Mrinmoy, Kale Ganesh D. Название: Water and Energy Management in India: Artificial Neural Networks and Multi-Criteria Decision Making Approaches ISBN: 3030666824 ISBN-13(EAN): 9783030666828 Издательство: Springer Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides an innovative, realistic and reliable solution to the common problem of Indian water and energy sector due to the onset of the Impact of Climate Change and Large-Scale Urbanization.
Автор: by Shashi Narayan, Claire Gardent Название: Deep Learning Approaches to Text Production ISBN: 1681737604 ISBN-13(EAN): 9781681737607 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 95170.00 T Наличие на складе: Нет в наличии. Описание: Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production is also at work in text-to-text transformations such as sentence compression, sentence fusion, paraphrasing, sentence (or text) simplification, and text summarisation. This book offers an overview of the fundamentals of neural models for text production. In particular, we elaborate on three main aspects of neural approaches to text production: how sequential decoders learn to generate adequate text, how encoders learn to produce better input representations, and how neural generators account for task-specific objectives. Indeed, each text-production task raises a slightly different challenge (e.g, how to take the dialogue context into account when producing a dialogue turn, how to detect and merge relevant information when summarising a text, or how to produce a well-formed text that correctly captures the information contained in some input data in the case of data-to-text generation). We outline the constraints specific to some of these tasks and examine how existing neural models account for them. More generally, this book considers text-to-text, meaning-to-text, and data-to-text transformations. It aims to provide the audience with a basic knowledge of neural approaches to text production and a roadmap to get them started with the related work. The book is mainly targeted at researchers, graduate students, and industrials interested in text production from different forms of inputs.
Автор: Karthikrajan Senthilnathan, Balamurugan Shanmugam, Dinesh Goyal, Iyswarya Annapoorani, Ravi Samikannu Название: Deep Learning Applications and Intelligent Decision Making in Engineering ISBN: 1799821099 ISBN-13(EAN): 9781799821090 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 166320.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is designed for engineers, computer scientists, programmers, software engineers, researchers, academics, and students.
Автор: Karthikrajan Senthilnathan, Balamurugan Shanmugam, Dinesh Goyal, Iyswarya Annapoorani, Ravi Samikannu Название: Deep Learning Applications and Intelligent Decision Making in Engineering ISBN: 1799821080 ISBN-13(EAN): 9781799821083 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 219910.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process.
Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.
Causality has been a subject of study for a long time. Often causality is confused with correlation. Human intuition has evolved such that it has learned to identify causality through correlation. In this book, four main themes are considered and these are causality, correlation, artificial intelligence and decision making. A correlation machine is defined and built using multi-layer perceptron network, principal component analysis, Gaussian Mixture models, genetic algorithms, expectation maximization technique, simulated annealing and particle swarm optimization. Furthermore, a causal machine is defined and built using multi-layer perceptron, radial basis function, Bayesian statistics and Hybrid Monte Carlo methods. Both these machines are used to build a Granger non-linear causality model. In addition, the Neyman-Rubin, Pearl and Granger causal models are studied and are unified. The automatic relevance determination is also applied to extend Granger causality framework to the non-linear domain. The concept of rational decision making is studied, and the theory of flexibly-bounded rationality is used to extend the theory of bounded rationality within the principle of the indivisibility of rationality. The theory of the marginalization of irrationality for decision making is also introduced to deal with satisficing within irrational conditions. The methods proposed are applied in biomedical engineering, condition monitoring and for modelling interstate conflict.
Автор: Narayan Shashi, Gardent Claire Название: Deep Learning Approaches to Text Production ISBN: 1681737582 ISBN-13(EAN): 9781681737584 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 75770.00 T Наличие на складе: Нет в наличии. Описание:
Text production has many applications. It is used, for instance, to generate dialogue turns from dialogue moves, verbalise the content of knowledge bases, or generate English sentences from rich linguistic representations, such as dependency trees or abstract meaning representations. Text production is also at work in text-to-text transformations such as sentence compression, sentence fusion, paraphrasing, sentence (or text) simplification, and text summarisation. This book offers an overview of the fundamentals of neural models for text production. In particular, we elaborate on three main aspects of neural approaches to text production: how sequential decoders learn to generate adequate text, how encoders learn to produce better input representations, and how neural generators account for task-specific objectives. Indeed, each text-production task raises a slightly different challenge (e.g, how to take the dialogue context into account when producing a dialogue turn, how to detect and merge relevant information when summarising a text, or how to produce a well-formed text that correctly captures the information contained in some input data in the case of data-to-text generation). We outline the constraints specific to some of these tasks and examine how existing neural models account for them. More generally, this book considers text-to-text, meaning-to-text, and data-to-text transformations. It aims to provide the audience with a basic knowledge of neural approaches to text production and a roadmap to get them started with the related work. The book is mainly targeted at researchers, graduate students, and industrials interested in text production from different forms of inputs.
Автор: Goldberg Yoav Название: Neural Network Methods in Natural Language Processing ISBN: 1627052984 ISBN-13(EAN): 9781627052986 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 76690.00 T Наличие на складе: Нет в наличии. Описание: Neural networks are a family of powerful machine learning models. This book focuses on the application of neural network models to natural language data. The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. It also covers the computation-graph abstraction, which allows to easily define and train arbitrary neural networks, and is the basis behind the design of contemporary neural network software libraries.The second part of the book (Parts III and IV) introduces more specialized neural network architectures, including 1D convolutional neural networks, recurrent neural networks, conditioned-generation models, and attention-based models. These architectures and techniques are the driving force behind state-of-the-art algorithms for machine translation, syntactic parsing, and many other applications. Finally, we also discuss tree-shaped networks, structured prediction, and the prospects of multi-task learning.
Автор: Silahtaroğlu Gцkhan, Dinзer Hasan, Yьksel Serhat Название: Data Science and Multiple Criteria Decision Making Approaches in Finance: Applications and Methods ISBN: 3030741753 ISBN-13(EAN): 9783030741754 Издательство: Springer Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.
Автор: Noorul Hassan Zardari; Kamal Ahmed; Sharif Moniruz Название: Weighting Methods and their Effects on Multi-Criteria Decision Making Model Outcomes in Water Resources Management ISBN: 3319125850 ISBN-13(EAN): 9783319125855 Издательство: Springer Рейтинг: Цена: 47880.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The book provides also a review of weighting methods applied in various multi-criteria decision-making (MCDM) methods and also presents survey results on priority ranking of watershed management criteria undertaken by 30 undergraduate and postgraduate students from the Faculty of Civil Engineering, Universiti Teknologi Malaysia.
Автор: Elsheikh, Ammar Hamed Название: Artificial Neural Networks For Renewable Energy Systems And Real-World Applications ISBN: 0128207930 ISBN-13(EAN): 9780128207932 Издательство: Elsevier Science Рейтинг: Цена: 144850.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Help students with education recovery by resolving gaps in knowledge and understanding and addressing misconceptions in GCSE 9-1 Combined Science. This authoritative Teacher Resource Pack accompanies Secure Science for GCSE Workbook and digital support online and on mobile to support teachers through the intervention sessions.
Автор: Vardan Mkrttchian, Ekaterina Aleshina, Leyla Gamidullaeva Название: Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms ISBN: 179981582X ISBN-13(EAN): 9781799815822 Издательство: Mare Nostrum (Eurospan) Цена: 180180.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Competition in today's global market offers strong motivation for the development of sophisticated tools within computer science. The neuron multi-functional technology platform is a developing field of study that regards the various interactive approaches that can be applied within this subject matter. As advancing technologies continue to emerge, managers and researchers need a compilation of research that discusses the advancements and specific implementations of these intelligent approaches with this platform. Avatar-Based Control, Estimation, Communications, and Development of Neuron Multi-Functional Technology Platforms is a pivotal reference source that provides vital research on the application of artificial and natural approaches towards neuron-based programs. While highlighting topics such as natural intelligence, neurolinguistics, and smart data storage, this publication presents techniques, case studies, and methodologies that combine the use of intelligent artificial and natural approaches with optimization techniques for facing problems and combines many types of hardware and software with a variety of communication technologies to enable the development of innovative applications. This book is ideally designed for researchers, practitioners, scientists, field experts, professors, and students seeking current research on the optimization of avatar-based advancements in multifaceted technology systems.
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