Learning Automata Approach for Social Networks, Alireza Rezvanian; Behnaz Moradabadi; Mina Ghavipo
Название: Evolutionary approach to machine learning and deep neural networks. ISBN: 9811301999 ISBN-13(EAN): 9789811301995 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gr?bner bases, relevance vector machines, transfer learning, bagging and boosting methods, clustering techniques (affinity propagation), and belief networks, among others. The development of such tools contributes to better optimizing methodologies. Beginning with the essentials of evolutionary algorithms and covering interdisciplinary research topics, the contents of this book are valuable for different classes of readers: novice, intermediate, and also expert readers from related fields.Following the chapters on introduction and basic methods, Chapter 3 details a new research direction, i.e., neuro-evolution, an evolutionary method for the generation of deep neural networks, and also describes how evolutionary methods are extended in combination with machine learning techniques. Chapter 4 includes novel methods such as particle swarm optimization based on affinity propagation (PSOAP), and transfer learning for differential evolution (TRADE), another machine learning approach for extending differential evolution.The last chapter is dedicated to the state of the art in gene regulatory network (GRN) research as one of the most interesting and active research fields. The author describes an evolving reaction network, which expands the neuro-evolution methodology to produce a type of genetic network suitable for biochemical systems and has succeeded in designing genetic circuits in synthetic biology. The author also presents real-world GRN application to several artificial intelligent tasks, proposing a framework of motion generation by GRNs (MONGERN), which evolves GRNs to operate a real humanoid robot.
Artificial Intelligence in the Age of Neural Networks and Brain Computing demonstrates that existing disruptive implications and applications of AI is a development of the unique attributes of neural networks, mainly machine learning, distributed architectures, massive parallel processing, black-box inference, intrinsic nonlinearity and smart autonomous search engines. The book covers the major basic ideas of brain-like computing behind AI, provides a framework to deep learning, and launches novel and intriguing paradigms as future alternatives. The success of AI-based commercial products proposed by top industry leaders, such as Google, IBM, Microsoft, Intel and Amazon can be interpreted using this book.
Developed from the 30th anniversary of the International Neural Network Society (INNS) and the 2017 International Joint Conference on Neural Networks (IJCNN)
Authored by top experts, global field pioneers and researchers working on cutting-edge applications in signal processing, speech recognition, games, adaptive control and decision-making
Edited by high-level academics and researchers in intelligent systems and neural networks
Автор: Zhang Название: Toward Deep Neural Networks ISBN: 1138387037 ISBN-13(EAN): 9781138387034 Издательство: Taylor&Francis Рейтинг: Цена: 127600.00 T Наличие на складе: Нет в наличии. Описание: This book introduces deep neural networks, with a focus on the weights-and-structure determination (WASD) algorithm. Based on the authors` 20 years of research experience on neuronets, the book explores the models, algorithms, and applications of the WASD neuronet.
Автор: Hollifield C. Ann, Wicks Jan LeBlanc, Sylvie George Название: Media Management: A Casebook Approach ISBN: 1138901024 ISBN-13(EAN): 9781138901025 Издательство: Taylor&Francis Рейтинг: Цена: 88800.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
Media Management: A Casebook Approach provides a detailed consideration of the manager's role in today's media organizations, highlighting critical skills and responsibilities. Using media-based cases that promote critical thinking and problem-solving, this text addresses topics of key concern to managers: diversity, group cultures, progressive discipline, training, and market-driven journalism, among others. The cases provide real-world scenarios to help students anticipate and prepare for experiences in their future careers.
Accounting for major changes in the media landscape that have affected every media industry, this Fifth Edition actively engages these changes in both discussion and cases. The text considers the need for managers to constantly adapt, obtain quality information, and be entrepreneurial and flexible in the face of new situations and technologies that cannot be predicted and change rapidly in national and international settings.
As a resource for students and young professionals working in media industries, Media Management offers essential insights and guidance for succeeding in contemporary media management roles.
Автор: McLean Paul Название: Culture in Networks ISBN: 0745687172 ISBN-13(EAN): 9780745687179 Издательство: Wiley Рейтинг: Цена: 19000.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Today, interest in networks is growing by leaps and bounds, in both scientific discourse and popular culture. Networks are thought to be everywhere from the architecture of our brains to global transportation systems.
Автор: Moolayil Jojo Название: Learn Keras for Deep Neural Networks: A Fast-Track Approach to Modern Deep Learning with Python ISBN: 1484242394 ISBN-13(EAN): 9781484242391 Издательство: Springer Рейтинг: Цена: 41920.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Learn, understand, and implement deep neural networks in a math- and programming-friendly approach using Keras and Python. The book focuses on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use-cases implemented in Keras.The overall book comprises three sections with two chapters in each section. The first section prepares you with all the necessary basics to get started in deep learning. Chapter 1 introduces you to the world of deep learning and its difference from machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be solved by supervised learning algorithms with deep neural networks. You’ll tackle one use case for regression and another for classification leveraging popular Kaggle datasets. Later, you will see an interesting and challenging part of deep learning: hyperparameter tuning; helping you further improve your models when building robust deep learning applications. Finally, you’ll further hone your skills in deep learning and cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks, you will have a thorough understanding of deep learning principles and have practical hands-on experience in developing enterprise-grade deep learning solutions in Keras.What You’ll Learn Master fast-paced practical deep learning concepts with math- and programming-friendly abstractions. Design, develop, train, validate, and deploy deep neural networks using the Keras framework Use best practices for debugging and validating deep learning models Deploy and integrate deep learning as a service into a larger software service or product Extend deep learning principles into other popular frameworks Who This Book Is For Software engineers and data engineers with basic programming skills in any language and who are keen on exploring deep learning for a career move or an enterprise project.
Автор: Heiko Hamann Название: Swarm Robotics: A Formal Approach ISBN: 3319892797 ISBN-13(EAN): 9783319892795 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides an introduction to Swarm Robotics, which is the application of methods from swarm intelligence to robotics. It goes on to present methods that allow readers to understand how to design large-scale robot systems by going through many example scenarios on topics such as aggregation, coordinated motion (flocking), task allocation, self-assembly, collective construction, and environmental monitoring. The author explains the methodology behind building multiple, simple robots and how the complexity emerges from the multiple interactions between these robots such that they are able to solve difficult tasks. The book can be used as a short textbook for specialized courses or as an introduction to Swarm Robotics for graduate students, researchers, and professionals who want a concise introduction to the field.
Автор: Hitoshi Iba Название: Evolutionary Approach to Machine Learning and Deep Neural Networks ISBN: 9811343586 ISBN-13(EAN): 9789811343582 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book provides theoretical and practical knowledge about a methodology for evolutionary algorithm-based search strategy with the integration of several machine learning and deep learning techniques. These include convolutional neural networks, Gr?bner bases, relevance vector machines, transfer learning, bagging and boosting methods, clustering techniques (affinity propagation), and belief networks, among others. The development of such tools contributes to better optimizing methodologies. Beginning with the essentials of evolutionary algorithms and covering interdisciplinary research topics, the contents of this book are valuable for different classes of readers: novice, intermediate, and also expert readers from related fields.Following the chapters on introduction and basic methods, Chapter 3 details a new research direction, i.e., neuro-evolution, an evolutionary method for the generation of deep neural networks, and also describes how evolutionary methods are extended in combination with machine learning techniques. Chapter 4 includes novel methods such as particle swarm optimization based on affinity propagation (PSOAP), and transfer learning for differential evolution (TRADE), another machine learning approach for extending differential evolution.The last chapter is dedicated to the state of the art in gene regulatory network (GRN) research as one of the most interesting and active research fields. The author describes an evolving reaction network, which expands the neuro-evolution methodology to produce a type of genetic network suitable for biochemical systems and has succeeded in designing genetic circuits in synthetic biology. The author also presents real-world GRN application to several artificial intelligent tasks, proposing a framework of motion generation by GRNs (MONGERN), which evolves GRNs to operate a real humanoid robot.
Автор: Ali Mohammad Saghiri; M. Daliri Khomami; Mohammad Название: Intelligent Random Walk: An Approach Based on Learning Automata ISBN: 3030108821 ISBN-13(EAN): 9783030108823 Издательство: Springer Рейтинг: Цена: 46570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book examines the intelligent random walk algorithms based on learning automata: these versions of random walk algorithms gradually obtain required information from the nature of the application to improve their efficiency. The book also describes the corresponding applications of this type of random walk algorithm, particularly as an efficient prediction model for large-scale networks such as peer-to-peer and social networks. The book opens new horizons for designing prediction models and problem-solving methods based on intelligent random walk algorithms, which are used for modeling and simulation in various types of networks, including computer, social and biological networks, and which may be employed a wide range of real-world applications.
This book presents a number of guidelines that are particularly useful in the context of decisions related to system-approach-based modern traffic engineering for the development of transport networks. Including practical examples and describing decision-making support systems it provides valuable insights for those seeking solutions to contemporary transport system problems on a daily basis, such as professional working for local authorities involved in planning urban and regional traffic development strategies as well as representatives of business and industry directly involved in implementing traffic engineering solutions. The guidelines provided enable readers to address problems in a timely manner and simplify the choice of appropriate strategies (including those connected with the relation between pedestrians and vehicle traffic flows, IT development in freight transport, safety issues related to accidents in road tunnels, but also open areas, like roundabouts and crossings). Furthermore, since the book also examines new theoretical-model approaches (including the model of arrival time distribution forming in a dense vehicle flow, the methodological basis of modelling and optimization of transport processes in the interaction of railways and maritime transport, traffic flow surveys and measurements, transport behaviour patterns, human factors in traffic engineering, and road condition modelling), it also appeals to researches and scientists studying these problems.
This book features selected papers submitted to and presented at the 16th Scientific and Technical Conference Transport Systems Theory and Practice organized by the Department of Transport Systems and Traffic Engineering at the Faculty of Transport of the Silesian University of Technology. The conference was held on 16-18 September 2019 in Katowice (Poland), more details at www.TSTP.polsl.pl.
Автор: Newman, Mark E. J. (anatol Rapoport Distinguished Название: Networks 2e hardback ISBN: 0198805098 ISBN-13(EAN): 9780198805090 Издательство: Oxford Academ Рейтинг: Цена: 72870.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book brings together recent advances and presents a comprehensive picture of the scientific study of networks. It includes discussion of computer networks, social networks, biological networks, and others, and an introduction to the mathematics of network theory, including analysis techniques, computer algorithms, and network modeling.
Автор: Chih-Lin I, Guanding Yu, Shuangfeng Han, Geoffrey Название: Green and Software-defined Wireless Networks: From Theory to Practice ISBN: 1108417329 ISBN-13(EAN): 9781108417327 Издательство: Cambridge Academ Рейтинг: Цена: 97150.00 T Наличие на складе: Поставка под заказ. Описание: An expert treatment of the state-of-the-art in green and soft communications, covering theory, 5G physical layer design, network architecture, energy efficient resource management strategies, and applications of wireless big data and artificial intelligence to wireless network design. Ideal for graduate students, professionals and researchers.
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