Evolutionary Approach to Machine Learning and Deep Neural Networks, Hitoshi Iba
Автор: Villa Название: Artificial Neural Networks and Machine Learning – ICANN 2016 ISBN: 3319447807 ISBN-13(EAN): 9783319447803 Издательство: Springer Рейтинг: Цена: 68950.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions.
Автор: Villa Название: Artificial Neural Networks and Machine Learning – ICANN 2016 ISBN: 3319447777 ISBN-13(EAN): 9783319447773 Издательство: Springer Рейтинг: Цена: 68950.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: The two volume set, LNCS 9886 + 9887, constitutes the proceedings of the 25th International Conference on Artificial Neural Networks, ICANN 2016, held in Barcelona, Spain, in September 2016. The 121 full papers included in this volume were carefully reviewed and selected from 227 submissions.
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.
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: Keller Название: Fundamentals of Computational Intelligence - Neural Networks, Fuzzy Systems, and Evolutionary Computation ISBN: 1119214343 ISBN-13(EAN): 9781119214342 Издательство: Wiley Рейтинг: Цена: 104550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation.
Автор: Takeshi Furuhashi; Yoshiki Uchikawa Название: Fuzzy Logic, Neural Networks, and Evolutionary Computation ISBN: 3540619887 ISBN-13(EAN): 9783540619888 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This volume contains a selection of 12 revised papers chosen from the 4th IEEE/Nagoya University World Wisepersons Workshop held in Nagoya, Japan, November 14-15, 1995. The papers presented are organized into sections including fuzzy and evolutionary computation, and fuzzy and learning automata.
Автор: Mirjalili Название: Evolutionary Algorithms and Neural Networks ISBN: 3319930249 ISBN-13(EAN): 9783319930244 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron.
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: S. Rajasekaran, G.A. Vijayalakshmi Pai Название: Neural Networks, Fuzzy Systems and Evolutionary Algorithms: Synthesis and Applications ISBN: 812035334X ISBN-13(EAN): 9788120353343 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 20330.00 T Наличие на складе: Невозможна поставка. Описание: Provides a comprehensive introduction to a consortium of technologies underlying soft computing. The constituent technologies discussed comprise neural network (NN), fuzzy system (FS), evolutionary algorithm (EA), and a number of hybrid systems, which include classes such as neuro-fuzzy, evolutionary-fuzzy, and neuro-evolutionary systems.
Автор: Seyedali Mirjalili Название: Evolutionary Algorithms and Neural Networks ISBN: 3030065723 ISBN-13(EAN): 9783030065720 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание:
This book introduces readers to the fundamentals of artificial neural networks, with a special emphasis on evolutionary algorithms. At first, the book offers a literature review of several well-regarded evolutionary algorithms, including particle swarm and ant colony optimization, genetic algorithms and biogeography-based optimization. It then proposes evolutionary version of several types of neural networks such as feed forward neural networks, radial basis function networks, as well as recurrent neural networks and multi-later perceptron. Most of the challenges that have to be addressed when training artificial neural networks using evolutionary algorithms are discussed in detail. The book also demonstrates the application of the proposed algorithms for several purposes such as classification, clustering, approximation, and prediction problems. It provides a tutorial on how to design, adapt, and evaluate artificial neural networks as well, and includes source codes for most of the proposed techniques as supplementary materials.
Автор: Wilkins Neil Название: Artificial Intelligence: An Essential Beginner`s Guide to AI, Machine Learning, Robotics, The Internet of Things, Neural Networks, Deep Learnin ISBN: 1950924807 ISBN-13(EAN): 9781950924806 Издательство: Неизвестно Рейтинг: Цена: 27580.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: So, what is the deal with intelligent machines? Will they soon decide on things such as copyright infringement? How about self-driving trucks and cars?What kind of impact will smart machines have on society and the future of human jobs?
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