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Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation, Daniela Sanchez; Patricia Melin


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Автор: Daniela Sanchez; Patricia Melin
Название:  Hierarchical Modular Granular Neural Networks with Fuzzy Aggregation
ISBN: 9783319288611
Издательство: Springer
Классификация:

ISBN-10: 331928861X
Обложка/Формат: Soft cover
Страницы: 101
Вес: 0.19 кг.
Дата издания: 02.03.2016
Серия: Springerbriefs in applied sciences and technology
Язык: English
Издание: 1st ed. 2016
Иллюстрации: 50 illustrations, color; 7 illustrations, black and white; viii, 101 p. 57 illus., 50 illus. in color.
Размер: 234 x 156 x 6
Читательская аудитория: General (us: trade)
Основная тема: Computational Intelligence
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: The techniquesused and combined in the proposed method are modular neural networks (MNNs)with a Granular Computing (GrC) approach, thus resulting in a new concept ofMNNs;


Hierarchical Type-2 Fuzzy Aggregation of Fuzzy Controllers

Автор: Leticia Cervantes; Oscar Castillo
Название: Hierarchical Type-2 Fuzzy Aggregation of Fuzzy Controllers
ISBN: 3319266705 ISBN-13(EAN): 9783319266701
Издательство: Springer
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Цена: 10480.00 р.
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Описание: Whenfuzzy logic is used it make it easy to performed the simulations, these fuzzysystems help to model the behavior of a real systems, using the fuzzysystems fuzzy rules are generated and with this can generate the behavior ofany variable depending on the inputs and linguistic value.

Aggregation Functions in Theory and in Practise

Автор: Humberto Bustince Sola; Javier Fernandez; Radko Me
Название: Aggregation Functions in Theory and in Practise
ISBN: 3642391648 ISBN-13(EAN): 9783642391644
Издательство: Springer
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Цена: 36570.00 р.
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Описание: This volume collects the extended abstracts of 45 contributions of participants to the Seventh International Summer School on Aggregation Operators (AGOP 2013), held at Pamplona in July, 16-20, 2013.

Hierarchical Neural Network Structures for Phoneme Recognition

Автор: Daniel Vasquez; Rainer Gruhn; Wolfgang Minker
Название: Hierarchical Neural Network Structures for Phoneme Recognition
ISBN: 3642344240 ISBN-13(EAN): 9783642344244
Издательство: Springer
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Цена: 18284.00 р.
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Описание: The subject of this study is the role of hierarchical structures, based on neural networks, in identifying phonemes in automated speech recognition systems. It shows how the artificial neural network paradigm can simplify the analysis of spoken language.

Hierarchical and Geometrical Methods in Scientific Visualization

Автор: Gerald Farin; Bernd Hamann; Hans Hagen
Название: Hierarchical and Geometrical Methods in Scientific Visualization
ISBN: 364262801X ISBN-13(EAN): 9783642628016
Издательство: Springer
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Цена: 20896.00 р.
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Описание: The nature of the physical Universe has been increasingly better understood in recent years, and cosmological concepts have undergone a rapid evolution (see, e.g., [11], [2],or [5]).

An Introduction to Data Analysis using Aggregation Functions in R

Автор: Simon James
Название: An Introduction to Data Analysis using Aggregation Functions in R
ISBN: 3319467611 ISBN-13(EAN): 9783319467610
Издательство: Springer
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Цена: 7965.00 р.
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Описание:

This textbook helps future data analysts comprehend aggregation function theory and methods in an accessible way, focusing on a fundamental understanding of the data and summarization tools. Offering a broad overview of recent trends in aggregation research, it complements any study in statistical or machine learning techniques. Readers will learn how to program key functions in R without obtaining an extensive programming background.
Sections of the textbook cover background information and context, aggregating data with averaging functions, power means, and weighted averages including the Borda count. It explains how to transform data using normalization or scaling and standardization, as well as log, polynomial, and rank transforms. The section on averaging with interaction introduces OWS functions and the Choquet integral, simple functions that allow the handling of non-independent inputs. The final chapters examine software analysis with an emphasis on parameter identification rather than technical aspects.
This textbook is designed for students studying computer science or business who are interested in tools for summarizing and interpreting data, without requiring a strong mathematical background. It is also suitable for those working on sophisticated data science techniques who seek a better conception of fundamental data aggregation. Solutions to the practice questions are included in the textbook.
Solving Network Design Problems via Decomposition, Aggregation and Approximation

Автор: B?rmann
Название: Solving Network Design Problems via Decomposition, Aggregation and Approximation
ISBN: 3658139129 ISBN-13(EAN): 9783658139124
Издательство: Springer
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Цена: 9141.00 р.
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Описание:

Andreas B?rmann develops novel approaches for the solution of network design problems as they arise in various contexts of applied optimization. At the example of an optimal expansion of the German railway network until 2030, the author derives a tailor-made decomposition technique for multi-period network design problems. Next, he develops a general framework for the solution of network design problems via aggregation of the underlying graph structure. This approach is shown to save much computation time as compared to standard techniques. Finally, the author devises a modelling framework for the approximation of the robust counterpart under ellipsoidal uncertainty, an often-studied case in the literature. Each of these three approaches opens up a fascinating branch of research which promises a better theoretical understanding of the problem and an increasing range of solvable application settings at the same time.
Markov chain aggregation for agent-based models

Автор: Banisch, Sven
Название: Markov chain aggregation for agent-based models
ISBN: 3319248758 ISBN-13(EAN): 9783319248752
Издательство: Springer
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Цена: 9781.00 р.
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Описание: This self-contained text develops a Markov chain approach that makes the rigorous analysis of a class of microscopic models that specify the dynamics of complex systems at the individual level possible.

Fuzzy Hierarchical Model for Risk Assessment

Автор: Hing Kai Chan; Xiaojun Wang
Название: Fuzzy Hierarchical Model for Risk Assessment
ISBN: 1447150422 ISBN-13(EAN): 9781447150428
Издательство: Springer
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Цена: 18284.00 р.
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Описание: This book offers a fuzzy-based hierarchical approach to risk management problems, tackling imprecise information with qualitative and quantitative criteria. Uses case studies from the food, fashion and electronics sectors on supply chain management and more.


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