Neural Network Data Analysis Using Simulnettm
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Neural Network Data Analysis Using Simulnettm
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Author : Edward J. Rzempoluck
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Neural Network Data Analysis Using Simulnettm written by Edward J. Rzempoluck and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
This book and software package complements the traditional data analysis tools already widely available. It presents an introduction to the analysis of data using neural network functions such as multilayer feed-forward networks using error back propagation, genetic algorithm-neural network hybrids, generalised regression neural networks, learning quantizer networks, and self-organising feature maps. In an easy-to-use, Windows-based environment it offers a wide range of data analytic tools which are not usually found together: genetic algorithms, probabilistic networks, as well as a number of related techniques that support these. Readers are assumed to have a basic understanding of computers and elementary mathematics, allowing them to quickly conduct sophisticated hands-on analyses of data sets.
Neural Network Data Analysis Using Simulnet
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Author : Rzempoluck EJ.
language : en
Publisher:
Release Date : 1998
Neural Network Data Analysis Using Simulnet written by Rzempoluck EJ. and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.
Human Interaction Emerging Technologies And Future Applications Iv
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Author : Tareq Ahram
language : en
Publisher: Springer Nature
Release Date : 2021-04-15
Human Interaction Emerging Technologies And Future Applications Iv written by Tareq Ahram and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-15 with Technology & Engineering categories.
This book reports on research and developments in human-technology interaction. A special emphasis is given to human-computer interaction, and its implementation for a wide range of purposes such as healthcare, manufacturing, transportation, and education, among others. The human aspects are analyzed in detail. Innovative studies related to human-centered design, wearable technologies, augmented, virtual and mixed reality simulation, as well as developments and applications of machine learning and AI for different purposes, represent the core of the book. Emerging issues in business, security, and infrastructure are also critically examined, thus offering a timely, scientifically-grounded, but also professionally-oriented snapshot of the current state of the field. The book is based on contributions presented at the 4th International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET-AI 2021, held on April 28-30, 2021, in Strasbourg, France. It offers a timely survey and a practice-oriented reference guide to researchers and professionals dealing with design and/or management of the new generation of service systems.
Neural Networks With R
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Author : Giuseppe Ciaburro
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-09-27
Neural Networks With R written by Giuseppe Ciaburro and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-27 with Computers categories.
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.
Bayesian Learning For Neural Networks
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Author : Radford M. Neal
language : en
Publisher: Springer
Release Date : 1996-08-09
Bayesian Learning For Neural Networks written by Radford M. Neal and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-08-09 with Mathematics categories.
Artificial "neural networks" are widely used as flexible models for classification and regression applications, but questions remain about how the power of these models can be safely exploited when training data is limited. This book demonstrates how Bayesian methods allow complex neural network models to be used without fear of the "overfitting" that can occur with traditional training methods. Insight into the nature of these complex Bayesian models is provided by a theoretical investigation of the priors over functions that underlie them. A practical implementation of Bayesian neural network learning using Markov chain Monte Carlo methods is also described, and software for it is freely available over the Internet. Presupposing only basic knowledge of probability and statistics, this book should be of interest to researchers in statistics, engineering, and artificial intelligence.
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Author :
language : zh-CN
Publisher:
Release Date : 2004
written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Electrical engineering categories.
Data Mining Using Neural Networks
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Author : Basilio De Braganca Pereira
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2012-07-01
Data Mining Using Neural Networks written by Basilio De Braganca Pereira and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-01 with Business & Economics categories.
A concise, easy-to-understand guide to using neural networks in data mining for mathematics, engineering, psychology, and computer science applications, this book compares how neural network models and statistical models are used to tackle data analysis problems. It focuses on the top of the hierarchy of the computational process and shows how neural networks can perform traditional statistical methods of analysis. The book includes some classical and Bayesian statistical inference results and employs R to illustrate the techniques.
Human Interaction Emerging Technologies And Future Applications Iv
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Author : Tareq Ahram
language : en
Publisher: Springer
Release Date : 2021-04-16
Human Interaction Emerging Technologies And Future Applications Iv written by Tareq Ahram and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-16 with Computers categories.
This book reports on research and developments in human-technology interaction. A special emphasis is given to human-computer interaction, and its implementation for a wide range of purposes such as healthcare, manufacturing, transportation, and education, among others. The human aspects are analyzed in detail. Innovative studies related to human-centered design, wearable technologies, augmented, virtual and mixed reality simulation, as well as developments and applications of machine learning and AI for different purposes, represent the core of the book. Emerging issues in business, security, and infrastructure are also critically examined, thus offering a timely, scientifically-grounded, but also professionally-oriented snapshot of the current state of the field. The book is based on contributions presented at the 4th International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET-AI 2021, held on April 28-30, 2021, in Strasbourg, France. Itoffers a timely survey and a practice-oriented reference guide to researchers and professionals dealing with design and/or management of the new generation of service systems.
Human Interaction And Emerging Technologies
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Author : Tareq Ahram
language : en
Publisher: Springer
Release Date : 2019-07-24
Human Interaction And Emerging Technologies written by Tareq Ahram and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-24 with Technology & Engineering categories.
This book reports on research and developments in human-technology interaction. A special emphasis is given to human-computer interaction, and its implementation for a wide range of purposes such as healthcare, aerospace, telecommunication, and education, among others. The human aspects are analyzed in detail. Timely studies on human-centered design, wearable technologies, social and affective computing, augmented, virtual and mixed reality simulation, human rehabilitation and biomechanics represent the core of the book. Emerging technology applications in business, security, and infrastructure are also critically examined, thus offering a timely, scientifically-grounded, but also professionally-oriented snapshot of the current state of the field. The book is based on contributions presented at the 1st International Conference on Human Interaction and Emerging Technologies, IHIET 2019, held on August 22-24, in Nice, France. It offers a timely survey and a practice-oriented reference guide to systems engineers, psychologists, sport scientists, physical therapists, as well as decision-makers, designing or dealing with the new generation of service systems. User Experience of a Social Media Based Knowledge Sharing System in Industry Work, Chapter of this book is available open access under a CC BY 4.0 license at link.springer.com
Knowledge Graphs
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Author : Aidan Hogan
language : en
Publisher: Springer Nature
Release Date : 2022-06-01
Knowledge Graphs written by Aidan Hogan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-01 with Computers categories.
This book provides a comprehensive and accessible introduction to knowledge graphs, which have recently garnered notable attention from both industry and academia. Knowledge graphs are founded on the principle of applying a graph-based abstraction to data, and are now broadly deployed in scenarios that require integrating and extracting value from multiple, diverse sources of data at large scale. The book defines knowledge graphs and provides a high-level overview of how they are used. It presents and contrasts popular graph models that are commonly used to represent data as graphs, and the languages by which they can be queried before describing how the resulting data graph can be enhanced with notions of schema, identity, and context. The book discusses how ontologies and rules can be used to encode knowledge as well as how inductive techniques—based on statistics, graph analytics, machine learning, etc.—can be used to encode and extract knowledge. It covers techniques for the creation, enrichment, assessment, and refinement of knowledge graphs and surveys recent open and enterprise knowledge graphs and the industries or applications within which they have been most widely adopted. The book closes by discussing the current limitations and future directions along which knowledge graphs are likely to evolve. This book is aimed at students, researchers, and practitioners who wish to learn more about knowledge graphs and how they facilitate extracting value from diverse data at large scale. To make the book accessible for newcomers, running examples and graphical notation are used throughout. Formal definitions and extensive references are also provided for those who opt to delve more deeply into specific topics.