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Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models, Treur Jan


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Автор: Treur Jan
Название:  Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models
ISBN: 9783030314477
Издательство: Springer
Классификация:





ISBN-10: 3030314472
Обложка/Формат: Paperback
Страницы: 412
Вес: 0.60 кг.
Дата издания: 13.11.2020
Язык: English
Размер: 23.39 x 15.60 x 2.24 cm
Ссылка на Издательство: Link
Поставляется из: Германии
Описание: Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily.


ADIGMA – A European Initiative on the Development of Adaptive Higher-Order Variational Methods for Aerospace Applications

Автор: Norbert Kroll; Heribert Bieler; Herman Deconinck;
Название: ADIGMA – A European Initiative on the Development of Adaptive Higher-Order Variational Methods for Aerospace Applications
ISBN: 3642264409 ISBN-13(EAN): 9783642264405
Издательство: Springer
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Цена: 61352.00 р.
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Описание: This volume contains results gained from the EU-funded 6th Framework project ADIGMA (Adaptive Higher-order Variational Methods for Aerodynamic Applications in Industry).

Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models

Автор: Jan Treur
Название: Network-Oriented Modeling for Adaptive Networks: Designing Higher-Order Adaptive Biological, Mental and Social Network Models
ISBN: 3030314448 ISBN-13(EAN): 9783030314446
Издательство: Springer
Рейтинг:
Цена: 13974.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Moreover, because adaptive networks are described in a network format as well, the approach can simply be applied iteratively, so that higher-order adaptive networks in which network adaptation itself is adaptive (second-order adaptation), too can be modeled just as easily.

Hands-On Deep Learning with R: A practical guide to designing, building, and improving neural network models using R

Автор: Pawlus Michael, Devine Rodger
Название: Hands-On Deep Learning with R: A practical guide to designing, building, and improving neural network models using R
ISBN: 1788996836 ISBN-13(EAN): 9781788996839
Издательство: Неизвестно
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Цена: 8091.00 р.
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Описание: Deep learning enables efficient and accurate learning from data. Developers working with R will be able to put their knowledge to work with this practical guide to deep learning. The book provides a hands-on approach to implementation and associated methodologies that will have you up-and-running, and productive in no time.

Adaptive Control with Recurrent High-order Neural Networks

Автор: George A. Rovithakis; Manolis A. Christodoulou
Название: Adaptive Control with Recurrent High-order Neural Networks
ISBN: 1447112016 ISBN-13(EAN): 9781447112013
Издательство: Springer
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Цена: 18167.00 р.
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Описание: The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies ...

Fractional-order Modeling of Nuclear Reactor: From Subdiffusive Neutron Transport to Control-oriented Models

Автор: Vishwesh Vyawahare; Paluri S. V. Nataraj
Название: Fractional-order Modeling of Nuclear Reactor: From Subdiffusive Neutron Transport to Control-oriented Models
ISBN: 9811356556 ISBN-13(EAN): 9789811356551
Издательство: Springer
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Цена: 16070.00 р.
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Описание: This book addresses the topic of fractional-order modeling of nuclear reactors. Approaching neutron transport in the reactor core as anomalous diffusion, specifically subdiffusion, it starts with the development of fractional-order neutron telegraph equations. Using a systematic approach, the book then examines the development and analysis of various fractional-order models representing nuclear reactor dynamics, ultimately leading to the fractional-order linear and nonlinear control-oriented models. The book utilizes the mathematical tool of fractional calculus, the calculus of derivatives and integrals with arbitrary non-integer orders (real or complex), which has recently been found to provide a more compact and realistic representation to the dynamics of diverse physical systems.Including extensive simulation results and discussing important issues related to the fractional-order modeling of nuclear reactors, the book offers a valuable resource for students and researchers working in the areas of fractional-order modeling and control and nuclear reactor modeling.

Fractional-order Modeling of Nuclear Reactor: From Subdiffusive Neutron Transport to Control-oriented Models

Автор: Vyawahare
Название: Fractional-order Modeling of Nuclear Reactor: From Subdiffusive Neutron Transport to Control-oriented Models
ISBN: 9811075867 ISBN-13(EAN): 9789811075865
Издательство: Springer
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Цена: 13974.00 р.
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Описание: Chapter 1. Fractional Calculus.- Chapter 2. Introduction to Nuclear Reactor Modeling.- Chapter 3. Development and Analysis of Fractional-order Neutron Telegraph Equation.- Chapter 4. Development and Analysis of Fractional-order Point Reactor Kinetics Model.- Chapter 5. Further Developments using Fractional-order Point Reactor Kinetics Model.- Chapter 6. Development and Analysis of Fractional-order Point Reactor Kinetics Models with Reactivity Feedback.- Chapter 7. Development and Analysis of Fractional-order Two-Group Models.

Artificial Higher Order Neural Networks for Modeling and Simulation

Автор: Ming Zhang
Название: Artificial Higher Order Neural Networks for Modeling and Simulation
ISBN: 1466621753 ISBN-13(EAN): 9781466621756
Издательство: Mare Nostrum (Eurospan)
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Цена: 28413.00 р.
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Описание: Artificial Higher Order Neural Networks for Modeling and Simulation introduces artificial Higher Order Neural Networks (HONNs) to professionals working in the fields of modeling and simulation, and explains that HONN is an open-box artificial neural network tool as compared to traditional artificial neural networks. Including details of the most popular HONN models, this book provides an opportunity for practitioners in the field of modeling and simulations to understand and know how to use HONNS in their area of expertise.


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