Neural Networks for Modelling and Control of Dynamic Systems
Author | : M. Norgaard |
Publisher | : |
Total Pages | : 246 |
Release | : 2003 |
Genre | : |
ISBN | : |
Download Neural Networks for Modelling and Control of Dynamic Systems Book in PDF, ePub and Kindle
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Neural Networks For Modelling And Control Of Dynamic Systems A Practitioners Handbook PDF full book. Access full book title Neural Networks For Modelling And Control Of Dynamic Systems A Practitioners Handbook.
Author | : M. Norgaard |
Publisher | : |
Total Pages | : 246 |
Release | : 2003 |
Genre | : |
ISBN | : |
Author | : Norgaard |
Publisher | : |
Total Pages | : 260 |
Release | : 2009-09-01 |
Genre | : |
ISBN | : 9788184893687 |
Author | : Juš Kocijan |
Publisher | : Springer |
Total Pages | : 267 |
Release | : 2015-11-21 |
Genre | : Technology & Engineering |
ISBN | : 3319210211 |
This monograph opens up new horizons for engineers and researchers in academia and in industry dealing with or interested in new developments in the field of system identification and control. It emphasizes guidelines for working solutions and practical advice for their implementation rather than the theoretical background of Gaussian process (GP) models. The book demonstrates the potential of this recent development in probabilistic machine-learning methods and gives the reader an intuitive understanding of the topic. The current state of the art is treated along with possible future directions for research. Systems control design relies on mathematical models and these may be developed from measurement data. This process of system identification, when based on GP models, can play an integral part of control design in data-based control and its description as such is an essential aspect of the text. The background of GP regression is introduced first with system identification and incorporation of prior knowledge then leading into full-blown control. The book is illustrated by extensive use of examples, line drawings, and graphical presentation of computer-simulation results and plant measurements. The research results presented are applied in real-life case studies drawn from successful applications including: a gas–liquid separator control; urban-traffic signal modelling and reconstruction; and prediction of atmospheric ozone concentration. A MATLAB® toolbox, for identification and simulation of dynamic GP models is provided for download.
Author | : Zhang, Ming |
Publisher | : IGI Global |
Total Pages | : 511 |
Release | : 2016-05-05 |
Genre | : Computers |
ISBN | : 1522500642 |
In recent years, Higher Order Neural Networks (HONNs) have been widely adopted by researchers for applications in control signal generating, pattern recognition, nonlinear recognition, classification, and predition of control and recognition scenarios. Due to the fact that HONNs have been proven to be faster, more accurate, and easier to explain than traditional neural networks, their applications are limitless. Applied Artificial Higher Order Neural Networks for Control and Recognition explores the ways in which higher order neural networks are being integrated specifically for intelligent technology applications. Emphasizing emerging research, practice, and real-world implementation, this timely reference publication is an essential reference source for researchers, IT professionals, and graduate-level computer science and engineering students.
Author | : Jorge D. Rios |
Publisher | : Academic Press |
Total Pages | : 160 |
Release | : 2020-01-15 |
Genre | : Science |
ISBN | : 0128170794 |
Neural Networks Modelling and Control: Applications for Unknown Nonlinear Delayed Systems in Discrete Time focuses on modeling and control of discrete-time unknown nonlinear delayed systems under uncertainties based on Artificial Neural Networks. First, a Recurrent High Order Neural Network (RHONN) is used to identify discrete-time unknown nonlinear delayed systems under uncertainties, then a RHONN is used to design neural observers for the same class of systems. Therefore, both neural models are used to synthesize controllers for trajectory tracking based on two methodologies: sliding mode control and Inverse Optimal Neural Control. As well as considering the different neural control models and complications that are associated with them, this book also analyzes potential applications, prototypes and future trends. Provide in-depth analysis of neural control models and methodologies Presents a comprehensive review of common problems in real-life neural network systems Includes an analysis of potential applications, prototypes and future trends
Author | : Zhang, Ming |
Publisher | : IGI Global |
Total Pages | : 455 |
Release | : 2012-10-31 |
Genre | : Computers |
ISBN | : 1466621761 |
"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 | : Zhang, Ming |
Publisher | : IGI Global |
Total Pages | : 540 |
Release | : 2021-02-05 |
Genre | : Computers |
ISBN | : 1799835650 |
Artificial neural network research is one of the new directions for new generation computers. Current research suggests that open box artificial higher order neural networks (HONNs) play an important role in this new direction. HONNs will challenge traditional artificial neural network products and change the research methodology that people are currently using in control and recognition areas for the control signal generating, pattern recognition, nonlinear recognition, classification, and prediction. Since HONNs are open box models, they can be easily accepted and used by individuals working in information science, information technology, management, economics, and business fields. Emerging Capabilities and Applications of Artificial Higher Order Neural Networks contains innovative research on how to use HONNs in control and recognition areas and explains why HONNs can approximate any nonlinear data to any degree of accuracy, their ease of use, and how they can have better nonlinear data recognition accuracy than SAS nonlinear procedures. Featuring coverage on a broad range of topics such as nonlinear regression, pattern recognition, and data prediction, this book is ideally designed for data analysists, IT specialists, engineers, researchers, academics, students, and professionals working in the fields of economics, business, modeling, simulation, control, recognition, computer science, and engineering research.
Author | : Konstantinos Diamantaras |
Publisher | : Springer Science & Business Media |
Total Pages | : 591 |
Release | : 2010-09-03 |
Genre | : Computers |
ISBN | : 3642158242 |
This three volume set LNCS 6352, LNCS 6353, and LNCS 6354 constitutes the refereed proceedings of the 20th International Conference on Artificial Neural Networks, ICANN 2010, held in Thessaloniki, Greece, in September 20010. The 102 revised full papers, 68 short papers and 29 posters presented were carefully reviewed and selected from 241 submissions. The third volume is divided in topical sections on classification – pattern recognition, learning algorithms and systems, computational intelligence, IEM3 workshop, CVA workshop, and SOINN workshop.
Author | : Management Association, Information Resources |
Publisher | : IGI Global |
Total Pages | : 1780 |
Release | : 2016-07-26 |
Genre | : Computers |
ISBN | : 1522507892 |
As technology continues to become more sophisticated, mimicking natural processes and phenomena also becomes more of a reality. Continued research in the field of natural computing enables an understanding of the world around us, in addition to opportunities for man-made computing to mirror the natural processes and systems that have existed for centuries. Nature-Inspired Computing: Concepts, Methodologies, Tools, and Applications takes an interdisciplinary approach to the topic of natural computing, including emerging technologies being developed for the purpose of simulating natural phenomena, applications across industries, and the future outlook of biologically and nature-inspired technologies. Emphasizing critical research in a comprehensive multi-volume set, this publication is designed for use by IT professionals, researchers, and graduate students studying intelligent computing.
Author | : Alkhatib, Ghazi I. |
Publisher | : IGI Global |
Total Pages | : 455 |
Release | : 2012-10-31 |
Genre | : Computers |
ISBN | : 1466621583 |
With the steady stream of new web based information technologies being introduced to organizations, the need for network and communication technologies to provide an easy integration of knowledge and information sharing is essential. Network and Communication Technology Innovations for Web and IT Advancement presents studies on trends, developments, and methods on information technology advancements through network and communication technology. This collection brings together integrated approaches for communication technology and usage for web and IT advancements.