Artificial Neural Nets Problem Solving Methods
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Artificial Neural Nets Problem Solving Methods
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Author : José Mira
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-05-22
Artificial Neural Nets Problem Solving Methods written by José Mira 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 2003-05-22 with Computers categories.
The two-volume set LNCS 2686 and LNCS 2687 constitute the refereed proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, held in Maó, Menorca, Spain in June 2003. The 197 revised papers presented were carefully reviewed and selected for inclusion in the book and address the following topics: mathematical and computational methods in neural modelling, neurophysiological data analysis and modelling, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, cognitive processes and artificial intelligence, methodologies for net design, bio-inspired systems and engineering, and applications in a broad variety of fields.
Artificial Neural Nets Problem Solving Methods
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Author : José Mira
language : en
Publisher:
Release Date : 2003
Artificial Neural Nets Problem Solving Methods written by José Mira and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Algorithms categories.
The four-volume set LNCS 2657, LNCS 2658, LNCS 2659, and LNCS 2660 constitutes the refereed proceedings of the Third International Conference on Computational Science, ICCS 2003, held concurrently in Melbourne, Australia and in St. Petersburg, Russia in June 2003. The four volumes present more than 460 reviewed contributed and invited papers and span the whole range of computational science, from foundational issues in computer science and algorithmic mathematics to advanced applications in virtually all application fields making use of computational techniques. These proceedings give a unique account of recent results in the field.
Artificial Neural Nets Problem Solving Methods
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Author : José Mira
language : en
Publisher: Springer
Release Date : 2014-03-12
Artificial Neural Nets Problem Solving Methods written by José Mira and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-12 with Computers categories.
Artificial Neural Nets Problem Solving Methods 7th International Work Conference On Artificial And Natural Neural Networks Iwann 2003 Ma Menorca Spain June 3 6 Proceedings
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Author : J Mira
language : en
Publisher:
Release Date : 2006
Artificial Neural Nets Problem Solving Methods 7th International Work Conference On Artificial And Natural Neural Networks Iwann 2003 Ma Menorca Spain June 3 6 Proceedings written by J Mira and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Artificial Neural Nets Problem Solving Methods
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Author : José Mira
language : en
Publisher: Springer
Release Date : 2003-08-03
Artificial Neural Nets Problem Solving Methods written by José Mira and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-08-03 with Computers categories.
The two-volume set LNCS 2686 and LNCS 2687 constitute the refereed proceedings of the 7th International Work-Conference on Artificial and Natural Neural Networks, IWANN 2003, held in MaÃ3, Menorca, Spain in June 2003.The 197 revised papers presented were carefully reviewed and selected for inclusion in the book and address the following topics: mathematical and computational methods in neural modelling, neurophysiological data analysis and modelling, structural and functional models of neurons, learning and other plasticity phenomena, complex systems dynamics, cognitive processes and artificial intelligence, methodologies for net design, bio-inspired systems and engineering, and applications in a broad variety of fields.nbsp;
An Introduction To Neural Network Methods For Differential Equations
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Author : Neha Yadav
language : en
Publisher: Springer
Release Date : 2015-02-26
An Introduction To Neural Network Methods For Differential Equations written by Neha Yadav and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-02-26 with Mathematics categories.
This book introduces a variety of neural network methods for solving differential equations arising in science and engineering. The emphasis is placed on a deep understanding of the neural network techniques, which has been presented in a mostly heuristic and intuitive manner. This approach will enable the reader to understand the working, efficiency and shortcomings of each neural network technique for solving differential equations. The objective of this book is to provide the reader with a sound understanding of the foundations of neural networks and a comprehensive introduction to neural network methods for solving differential equations together with recent developments in the techniques and their applications. The book comprises four major sections. Section I consists of a brief overview of differential equations and the relevant physical problems arising in science and engineering. Section II illustrates the history of neural networks starting from their beginnings in the 1940s through to the renewed interest of the 1980s. A general introduction to neural networks and learning technologies is presented in Section III. This section also includes the description of the multilayer perceptron and its learning methods. In Section IV, the different neural network methods for solving differential equations are introduced, including discussion of the most recent developments in the field. Advanced students and researchers in mathematics, computer science and various disciplines in science and engineering will find this book a valuable reference source.
Neural Networks In Optimization
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Author : Xiang-Sun Zhang
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Neural Networks In Optimization written by Xiang-Sun Zhang 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 2013-03-09 with Science categories.
People are facing more and more NP-complete or NP-hard problems of a combinatorial nature and of a continuous nature in economic, military and management practice. There are two ways in which one can enhance the efficiency of searching for the solutions of these problems. The first is to improve the speed and memory capacity of hardware. We all have witnessed the computer industry's amazing achievements with hardware and software developments over the last twenty years. On one hand many computers, bought only a few years ago, are being sent to elementary schools for children to learn the ABC's of computing. On the other hand, with economic, scientific and military developments, it seems that the increase of intricacy and the size of newly arising problems have no end. We all realize then that the second way, to design good algorithms, will definitely compensate for the hardware limitations in the case of complicated problems. It is the collective and parallel computation property of artificial neural net works that has activated the enthusiasm of researchers in the field of computer science and applied mathematics. It is hard to say that artificial neural networks are solvers of the above-mentioned dilemma, but at least they throw some new light on the difficulties we face. We not only anticipate that there will be neural computers with intelligence but we also believe that the research results of artificial neural networks might lead to new algorithms on von Neumann's computers.
Research Anthology On Artificial Neural Network Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2021-07-16
Research Anthology On Artificial Neural Network Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-16 with Computers categories.
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.
Applied Artificial Neural Network Methods For Engineers And Scientists Solving Algebraic Equations
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Author : Snehashish Chakraverty
language : en
Publisher: World Scientific
Release Date : 2021-01-26
Applied Artificial Neural Network Methods For Engineers And Scientists Solving Algebraic Equations written by Snehashish Chakraverty and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-26 with Computers categories.
The aim of this book is to handle different application problems of science and engineering using expert Artificial Neural Network (ANN). As such, the book starts with basics of ANN along with different mathematical preliminaries with respect to algebraic equations. Then it addresses ANN based methods for solving different algebraic equations viz. polynomial equations, diophantine equations, transcendental equations, system of linear and nonlinear equations, eigenvalue problems etc. which are the basic equations to handle the application problems mentioned in the content of the book. Although there exist various methods to handle these problems, but sometimes those may be problem dependent and may fail to give a converge solution with particular discretization. Accordingly, ANN based methods have been addressed here to solve these problems. Detail ANN architecture with step by step procedure and algorithm have been included. Different example problems are solved with respect to various application and mathematical problems. Convergence plots and/or convergence tables of the solutions are depicted to show the efficacy of these methods. It is worth mentioning that various application problems viz. Bakery problem, Power electronics applications, Pole placement, Electrical Network Analysis, Structural engineering problem etc. have been solved using the ANN based methods.
Artificial Neural Nets And Genetic Algorithms
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Author : David W. Pearson
language : en
Publisher: Springer Science & Business Media
Release Date : 2003-04-08
Artificial Neural Nets And Genetic Algorithms written by David W. Pearson 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 2003-04-08 with Computers categories.
The papers in this volume present theoretical aspects and applications of artificial neural networks and genetic algorithms. Also included are papers on fuzzy logic, soft computing, and artificial intelligence. Fundamental issues are addressed, such as the nonlinear approximation capabilities of neural networks and formal methods of data representation with topological properties. New elements in genetic algorithms are presented, for example, crossover methods and gene representation. Papers on applications of neural networks show how successful these methods are in a wide range of fields like meteorological and atmospheric pollution forecasts, furnace control, and system identification. Genetic algorithms are used to solve optimization problems related to shipping and computer vision. Fuzzy-logic-based techniques are applied to sociodynamic models and hybrid neuro-fuzzy models.