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Combining Artificial Neural Nets

Combining Artificial Neural Nets
Author: Amanda J.C. Sharkey
Publisher: Springer Science & Business Media
Total Pages: 300
Release: 2012-12-06
Genre: Computers
ISBN: 1447107934

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This volume, written by leading researchers, presents methods of combining neural nets to improve their performance. The techniques include ensemble-based approaches, where a variety of methods are used to create a set of different nets trained on the same task, and modular approaches, where a task is decomposed into simpler problems. The techniques are also accompanied by an evaluation of their relative effectiveness and their application to a variety of problems.


Growing Adaptive Machines

Growing Adaptive Machines
Author: Taras Kowaliw
Publisher: Springer
Total Pages: 266
Release: 2014-06-04
Genre: Technology & Engineering
ISBN: 3642553370

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The pursuit of artificial intelligence has been a highly active domain of research for decades, yielding exciting scientific insights and productive new technologies. In terms of generating intelligence, however, this pursuit has yielded only limited success. This book explores the hypothesis that adaptive growth is a means of moving forward. By emulating the biological process of development, we can incorporate desirable characteristics of natural neural systems into engineered designs and thus move closer towards the creation of brain-like systems. The particular focus is on how to design artificial neural networks for engineering tasks. The book consists of contributions from 18 researchers, ranging from detailed reviews of recent domains by senior scientists, to exciting new contributions representing the state of the art in machine learning research. The book begins with broad overviews of artificial neurogenesis and bio-inspired machine learning, suitable both as an introduction to the domains and as a reference for experts. Several contributions provide perspectives and future hypotheses on recent highly successful trains of research, including deep learning, the Hyper NEAT model of developmental neural network design, and a simulation of the visual cortex. Other contributions cover recent advances in the design of bio-inspired artificial neural networks, including the creation of machines for classification, the behavioural control of virtual agents, the desi gn of virtual multi-component robots and morphologies and the creation of flexible intelligence. Throughout, the contributors share their vast expertise on the means and benefits of creating brain-like machines. This book is appropriate for advanced students and practitioners of artificial intelligence and machine learning.


Neural Networks with R

Neural Networks with R
Author: Giuseppe Ciaburro
Publisher: Packt Publishing Ltd
Total Pages: 270
Release: 2017-09-27
Genre: Computers
ISBN: 1788399412

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Uncover the power of artificial neural networks by implementing them through R code. About This Book Develop a strong background in neural networks with R, to implement them in your applications Build smart systems using the power of deep learning Real-world case studies to illustrate the power of neural network models Who This Book Is For This book is intended for anyone who has a statistical background with knowledge in R and wants to work with neural networks to get better results from complex data. If you are interested in artificial intelligence and deep learning and you want to level up, then this book is what you need! What You Will Learn Set up R packages for neural networks and deep learning Understand the core concepts of artificial neural networks Understand neurons, perceptrons, bias, weights, and activation functions Implement supervised and unsupervised machine learning in R for neural networks Predict and classify data automatically using neural networks Evaluate and fine-tune the models you build. In Detail Neural networks are one of the most fascinating machine learning models for solving complex computational problems efficiently. Neural networks are used to solve wide range of problems in different areas of AI and machine learning. This book explains the niche aspects of neural networking and provides you with foundation to get started with advanced topics. The book begins with neural network design using the neural net package, then you'll build a solid foundation knowledge of how a neural network learns from data, and the principles behind it. This book covers various types of neural network including recurrent neural networks and convoluted neural networks. You will not only learn how to train neural networks, but will also explore generalization of these networks. Later we will delve into combining different neural network models and work with the real-world use cases. By the end of this book, you will learn to implement neural network models in your applications with the help of practical examples in the book. Style and approach A step-by-step guide filled with real-world practical examples.


Classic Works of the Dempster-Shafer Theory of Belief Functions

Classic Works of the Dempster-Shafer Theory of Belief Functions
Author: Ronald R. Yager
Publisher: Springer
Total Pages: 813
Release: 2008-01-22
Genre: Technology & Engineering
ISBN: 354044792X

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This is a collection of classic research papers on the Dempster-Shafer theory of belief functions. The book is the authoritative reference in the field of evidential reasoning and an important archival reference in a wide range of areas including uncertainty reasoning in artificial intelligence and decision making in economics, engineering, and management. The book includes a foreword reflecting the development of the theory in the last forty years.


Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering

Foundations of Neural Networks, Fuzzy Systems, and Knowledge Engineering
Author: Nikola K. Kasabov
Publisher: Marcel Alencar
Total Pages: 581
Release: 1996
Genre: Artificial intelligence
ISBN: 0262112124

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Combines the study of neural networks and fuzzy systems with symbolic artificial intelligence (AI) methods to build comprehensive AI systems. Describes major AI problems (pattern recognition, speech recognition, prediction, decision-making, game-playing) and provides illustrative examples. Includes applications in engineering, business and finance.


Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools

Explainable Neural Networks Based on Fuzzy Logic and Multi-criteria Decision Tools
Author: József Dombi
Publisher: Springer Nature
Total Pages: 186
Release: 2021-04-28
Genre: Technology & Engineering
ISBN: 3030722805

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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. Fuzzy logic together with multi-criteria decision-making tools provides very powerful tools for modeling human thinking. Based on their common theoretical basis, we propose a consistent framework for modeling human thinking by using the tools of all three fields: fuzzy logic, multi-criteria decision-making, and deep learning to help reduce the black-box nature of neural models; a challenge that is of vital importance to the whole research community.


Artificial Neural Networks in Finance and Manufacturing

Artificial Neural Networks in Finance and Manufacturing
Author: Kamruzzaman, Joarder
Publisher: IGI Global
Total Pages: 299
Release: 2006-03-31
Genre: Computers
ISBN: 1591406722

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"This book presents a variety of practical applications of neural networks in two important domains of economic activity: finance and manufacturing"--Provided by publisher.


Applications and Science in Soft Computing

Applications and Science in Soft Computing
Author: Ahmad Lotfi
Publisher: Springer Science & Business Media
Total Pages: 351
Release: 2013-06-29
Genre: Computers
ISBN: 3540452400

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Soft computing techniques have reached a significant level of recognition and - ceptance from both the academic and industrial communities. The papers collected in this volume illustrate the depth of the current theoretical research trends and the breadth of the application areas in which soft computing methods are making c- tributions. This volume consists of forty six selected papers presented at the Fourth Inter- tional Conference on Recent Advances in Soft Computing, which was held in N- th th tingham, United Kingdom on 12 and 13 December 2002 at Nottingham Trent University. This volume is organized in five parts. The first four parts address mainly the f- damental and theoretical advances in soft computing, namely Artificial Neural Networks, Evolutionary Computing, Fuzzy Systems and Hybrid Systems. The fifth part of this volume presents papers that deal with practical issues and ind- trial applications of soft computing techniques. We would like to express our sincere gratitude to all the authors who submitted contributions for inclusion. We are also indebted to Janusz Kacprzyk for his - vices related to this volume. We hope you find the volume an interesting refl- tion of current theoretical and application based soft computing research.


Research Anthology on Artificial Neural Network Applications

Research Anthology on Artificial Neural Network Applications
Author: Management Association, Information Resources
Publisher: IGI Global
Total Pages: 1575
Release: 2021-07-16
Genre: Computers
ISBN: 1668424096

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Artificial neural networks (ANNs) present many benefits in analyzing complex data in a proficient manner. As an effective and efficient problem-solving method, ANNs are incredibly useful in many different fields. From education to medicine and banking to engineering, artificial neural networks are a growing phenomenon as more realize the plethora of uses and benefits they provide. Due to their complexity, it is vital for researchers to understand ANN capabilities in various fields. The Research Anthology on Artificial Neural Network Applications covers critical topics related to artificial neural networks and their multitude of applications in a number of diverse areas including medicine, finance, operations research, business, social media, security, and more. Covering everything from the applications and uses of artificial neural networks to deep learning and non-linear problems, this book is ideal for computer scientists, IT specialists, data scientists, technologists, business owners, engineers, government agencies, researchers, academicians, and students, as well as anyone who is interested in learning more about how artificial neural networks can be used across a wide range of fields.


Encyclopedia of Computer Science and Technology

Encyclopedia of Computer Science and Technology
Author: Allen Kent
Publisher: CRC Press
Total Pages: 408
Release: 2000-04-28
Genre: Computers
ISBN: 9780824722951

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Combining Artificial Neural Networks to Symbolic and Algebraic computation