Neural Networks And Simulation Methods

Author : Wu
Publisher : CRC Press
ISBN 13 : 9780824791810
Total Pages : 452 pages
Book Rating : 4.19/5 ( download)

DOWNLOAD NOW!

Download or read book Neural Networks and Simulation Methods written by Wu and published by CRC Press. This book was released on 1993-12-14 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work explains network dynamics, learning paradigms, and computational capabilities of feedforward, self-organization, and feedback neural network models-addressing specific problems such as data fusion and data modeling. It goes on to describe a neural network simulation software package - USTCNET and gives some segments of the program.

Author : Zhang, Ming
Publisher : IGI Global
ISBN 13 : 1466621761
Total Pages : 455 pages
Book Rating : 4.63/5 ( download)

DOWNLOAD NOW!

Download or read book Artificial Higher Order Neural Networks for Modeling and Simulation written by Zhang, Ming and published by IGI Global. This book was released on 2012-10-31 with total page 455 pages. Available in PDF, EPUB and Kindle. Book excerpt: "This book introduces Higher Order Neural Networks (HONNs) to computer scientists and computer engineers as an open box neural networks tool when compared to traditional artificial neural networks"--Provided by publisher.

Author : Timon Rabczuk
Publisher : Springer Nature
ISBN 13 : 3031366441
Total Pages : 456 pages
Book Rating : 4.44/5 ( download)

DOWNLOAD NOW!

Download or read book Machine Learning in Modeling and Simulation written by Timon Rabczuk and published by Springer Nature. This book was released on 2023-11-04 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning (ML) approaches have been extensively and successfully employed in various areas, like in economics, medical predictions, face recognition, credit card fraud detection, and spam filtering. There is clearly also the potential that ML techniques developed in Engineering and the Sciences will drastically increase the possibilities of analysis and accelerate the design to analysis time. With the use of ML techniques, coupled to conventional methods like finite element and digital twin technologies, new avenues of modeling and simulation can be opened but the potential of these ML techniques needs to still be fully harvested, with the methods developed and enhanced. The objective of this book is to provide an overview of ML in Engineering and the Sciences presenting fundamental theoretical ingredients with a focus on the next generation of computer modeling in Engineering and the Sciences in which the exciting aspects of machine learning are incorporated. The book is of value to any researcher and practitioner interested in research or applications of ML in the areas of scientific modeling and computer aided engineering.

Author : Rob J Hyndman
Publisher : OTexts
ISBN 13 : 0987507117
Total Pages : 380 pages
Book Rating : 4.12/5 ( download)

DOWNLOAD NOW!

Download or read book Forecasting: principles and practice written by Rob J Hyndman and published by OTexts. This book was released on 2018-05-08 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Author : Michael R. Berthold
Publisher : Springer
ISBN 13 : 9783030445836
Total Pages : 588 pages
Book Rating : 4.36/5 ( download)

DOWNLOAD NOW!

Download or read book Advances in Intelligent Data Analysis XVIII written by Michael R. Berthold and published by Springer. This book was released on 2020-04-02 with total page 588 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.

Author : Genki Yagawa
Publisher : Springer Nature
ISBN 13 : 3030661113
Total Pages : 233 pages
Book Rating : 4.13/5 ( download)

DOWNLOAD NOW!

Download or read book Computational Mechanics with Neural Networks written by Genki Yagawa and published by Springer Nature. This book was released on 2021-02-26 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book shows how neural networks are applied to computational mechanics. Part I presents the fundamentals of neural networks and other machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems of computational mechanics. The final chapter gives perspectives to the applications of the deep learning to computational mechanics.

Author : Stefanie Czischek
Publisher : Springer Nature
ISBN 13 : 3030527158
Total Pages : 205 pages
Book Rating : 4.50/5 ( download)

DOWNLOAD NOW!

Download or read book Neural-Network Simulation of Strongly Correlated Quantum Systems written by Stefanie Czischek and published by Springer Nature. This book was released on 2020-08-27 with total page 205 pages. Available in PDF, EPUB and Kindle. Book excerpt: Quantum systems with many degrees of freedom are inherently difficult to describe and simulate quantitatively. The space of possible states is, in general, exponentially large in the number of degrees of freedom such as the number of particles it contains. Standard digital high-performance computing is generally too weak to capture all the necessary details, such that alternative quantum simulation devices have been proposed as a solution. Artificial neural networks, with their high non-local connectivity between the neuron degrees of freedom, may soon gain importance in simulating static and dynamical behavior of quantum systems. Particularly promising candidates are neuromorphic realizations based on analog electronic circuits which are being developed to capture, e.g., the functioning of biologically relevant networks. In turn, such neuromorphic systems may be used to measure and control real quantum many-body systems online. This thesis lays an important foundation for the realization of quantum simulations by means of neuromorphic hardware, for using quantum physics as an input to classical neural nets and, in turn, for using network results to be fed back to quantum systems. The necessary foundations on both sides, quantum physics and artificial neural networks, are described, providing a valuable reference for researchers from these different communities who need to understand the foundations of both.

Author : Josef Skrzypek
Publisher : Springer Science & Business Media
ISBN 13 : 1461527368
Total Pages : 263 pages
Book Rating : 4.67/5 ( download)

DOWNLOAD NOW!

Download or read book Neural Network Simulation Environments written by Josef Skrzypek and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural Network Simulation Environments describes some of the best examples of neural simulation environments. All current neural simulation tools can be classified into four overlapping categories of increasing sophistication in software engineering. The least sophisticated are undocumented and dedicated programs, developed to solve just one specific problem; these tools cannot easily be used by the larger community and have not been included in this volume. The next category is a collection of custom-made programs, some perhaps borrowed from other application domains, and organized into libraries, sometimes with a rudimentary user interface. More recently, very sophisticated programs started to appear that integrate advanced graphical user interface and other data analysis tools. These are frequently dedicated to just one neural architecture/algorithm as, for example, three layers of interconnected artificial `neurons' learning to generalize input vectors using a backpropagation algorithm. Currently, the most sophisticated simulation tools are complete, system-level environments, incorporating the most advanced concepts in software engineering that can support experimentation and model development of a wide range of neural networks. These environments include sophisticated graphical user interfaces as well as an array of tools for analysis, manipulation and visualization of neural data. Neural Network Simulation Environments is an excellent reference for researchers in both academia and industry, and can be used as a text for advanced courses on the subject.

Author : Lazaros Iliadis
Publisher : Springer
ISBN 13 : 331923983X
Total Pages : 402 pages
Book Rating : 4.35/5 ( download)

DOWNLOAD NOW!

Download or read book Engineering Applications of Neural Networks written by Lazaros Iliadis and published by Springer. This book was released on 2015-09-28 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 16th International Conference on Engineering Applications of Neural Networks, EANN 2015, held in Rhodes, Greece, in September 2015. The 36 revised full papers presented together with the abstracts of three invited talks and two tutorials were carefully reviewed and selected from 84 submissions. The papers are organized in topical sections on industrial-engineering applications of ANN; bioinformatics; intelligent medical modeling; life-earth sciences intelligent modeling; learning-algorithms; intelligent telecommunications modeling; fuzzy modeling; robotics and control; smart cameras; pattern recognition-facial mapping; classification; financial intelligent modeling; echo state networks.

Author : Fuliang Yin
Publisher : Springer
ISBN 13 : 3540286489
Total Pages : 1054 pages
Book Rating : 4.86/5 ( download)

DOWNLOAD NOW!

Download or read book Advances in Neural Networks - ISNN 2004 written by Fuliang Yin and published by Springer. This book was released on 2011-04-07 with total page 1054 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the International Symposium on Neural N- works (ISNN 2004) held in Dalian, Liaoning, China duringAugust 19–21, 2004. ISNN 2004 received over 800 submissions from authors in ?ve continents (Asia, Europe, North America, South America, and Oceania), and 23 countries and regions (mainland China, Hong Kong, Taiwan, South Korea, Japan, Singapore, India, Iran, Israel, Turkey, Hungary, Poland, Germany, France, Belgium, Spain, UK, USA, Canada, Mexico, - nezuela, Chile, andAustralia). Based on reviews, the Program Committee selected 329 high-quality papers for presentation at ISNN 2004 and publication in the proceedings. The papers are organized into many topical sections under 11 major categories (theo- tical analysis; learning and optimization; support vector machines; blind source sepa- tion,independentcomponentanalysis,andprincipalcomponentanalysis;clusteringand classi?cation; robotics and control; telecommunications; signal, image and time series processing; detection, diagnostics, and computer security; biomedical applications; and other applications) covering the whole spectrum of the recent neural network research and development. In addition to the numerous contributed papers, ?ve distinguished scholars were invited to give plenary speeches at ISNN 2004. ISNN 2004 was an inaugural event. It brought together a few hundred researchers, educators,scientists,andpractitionerstothebeautifulcoastalcityDalianinnortheastern China. It provided an international forum for the participants to present new results, to discuss the state of the art, and to exchange information on emerging areas and future trends of neural network research. It also created a nice opportunity for the participants to meet colleagues and make friends who share similar research interests.