Water and Energy Management in India: Artificial Neural Networks and Multi-Criteria Decision Making Approaches, Majumder Mrinmoy, Kale Ganesh D.
Автор: Aminzadeh Fred, Sandham W., Leggett M. Название: Geophysical Applications of Artificial Neural Networks and Fuzzy Logic ISBN: 1402017294 ISBN-13(EAN): 9781402017292 Издательство: Springer Рейтинг: Цена: 121110.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book is the first major text to encompass the wide diversity of geophysical applications of artificial neural networks (ANNs) and fuzzy logic (FZ). Each chapter, written by internationally-renowned experts in their field, represents a specific geophysical application, ranging from first-break picking and trace editing encountered in seismic exploration, through well-log lithology determination, to electromagnetic exploration and earthquake seismology. The book offers a well-balanced division of contributions from industry and academia, and includes a comprehensive, up-to-date bibliography covering all major publications in geophysical applications of ANNs and FZ. A special feature of this volume is the preface written by Professor Fred Aminzadeh, eminent authority in the field of artificial intelligence and geophysics. The enclosed CD-ROM contains full colour figures and searchable files, as well as short biographies of the editors.
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: 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: 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: Dombi Jуzsef, Csiszбr Orsolya Название: Explainable Neural Networks Based on Fuzzy Logic and Multi-Criteria Decision Tools ISBN: 3030722791 ISBN-13(EAN): 9783030722791 Издательство: Springer Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The research presented in this book shows how combining deep neural networks with a special class of fuzzy logical rules and multi-criteria decision tools can make deep neural networks more interpretable - and even, in many cases, more efficient.
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: Mauro Tosta, Gast?o Soares de Moura Filho, Leandro Название: Decision Making in Dental Implantology: Atlas of Surgical and Restorative Approaches ISBN: 1119225949 ISBN-13(EAN): 9781119225942 Издательство: Wiley Рейтинг: Цена: 164680.00 T Наличие на складе: Поставка под заказ. Описание: Decision Making in Dental Implantology: Atlas of Surgical and Restorative Approaches offers an image-based resource to both the surgical and restorative aspects of implant therapy, presenting more than 2,000 color images with an innovative case-by-case approach.
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: 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: 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.
