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Download Intelligent Engineering Systems and Computational Cybernetics fb2, epub

by J.A. Tenreiro Machado,Béla Pátkai,Imre J. Rudas

Download Intelligent Engineering Systems and Computational Cybernetics fb2, epub

ISBN: 1402086776
Author: J.A. Tenreiro Machado,Béla Pátkai,Imre J. Rudas
Language: English
Publisher: Springer; 2009 edition (February 9, 2009)
Pages: 460
Category: Computer Science
Subcategory: IT
Rating: 4.5
Votes: 924
Size Fb2: 1324 kb
Size ePub: 1789 kb
Size Djvu: 1665 kb
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Intelligent Engineering Systems and Computational Cybernetics. J. A. Tenreiro Machado, Béla Pátkai, Imre J. Rudas.

Intelligent Engineering Systems and Computational Cybernetics. Intelligent Engineering Systems and Computational Cybernetics. Скачать (pdf, 2. 2 Mb).

Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling.

State of the art in the subject. price for USA in USD (gross). Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling. The conventional analytical techniques-based approaches for describing and predicting the behaviour of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model.

José A. Tenreiro Machado

José A. Tenreiro Machado. Fractional calculus (FC) is widely used in most areas of science and engineering, being recognized its ability to yield a superior modeling and control in many dynamical systems. In this perspective, this article illustrates two applications of FC in the area of control systems.

Computational Cybernetics – E-book de . Today, the two complementary branches of Machine Intelligence, that is, Artificial Intelligence and Computational Intelligence serve as the basis of Intelligent Engineering Systems.

Intelligent Engineering Systems and Computational Cybernetics – E-book de . The huge number of scientific results published in Journal and conference proceedings worldwide substantiates this statement. The present book contains several articles taking different viewpoints in the field of intelligent systems.

Relationship between Complex Systematic Concepts, by Mohamed H. Al-Kuwaiti, Nicholas Kyriakopoulos; Particle Swarm Design of Digital Circuits, by Cecilia Reis and . Tenreiro Machado; From Cybernetics to Plectics: a Practical Approach to Systems Enquiry in Engineering, by Bela Patkai, Jozsef K. Tar, Imre J. Rudas; Part VI Mathematical Methods and Models; Extending the Spatial RelationalModel PLA to Represent Trees, by Agnes.

Описание: Computational Intelligence for Engineering Systems provides an overview and original analysis of new developments and advances in several areas of computational intelligence. Computational Intelligence have become the road-map for engineers to develop and analyze novel techniques to solve problems in basic sciences (such as physics, chemistry and biology) and engineering, environmental, life and social sciences.

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Engineering practice often has to deal with complex systems of multiple variable and multiple parameter models almost always with strong non-linear coupling. The conventional analytical techniques-based approaches for describing and predicting the behaviour of such systems in many cases are doomed to failure from the outset, even in the phase of the construction of a more or less appropriate mathematical model. These approaches normally are too categorical in the sense that in the name of “modelling accuracy” they try to describe all the structural details of the real physical system to be modelled. This can significantly increase the intricacy of the model and may result in a enormous computational burden without achieving considerable improvement of the solution. The best paradigm exemplifying this situation may be the classic perturbation theory: the less significant the achievable correction, the more work has to be invested to obtain it.

A further important component of machine intelligence is a kind of “structural uniformity” giving room and possibility to model arbitrary particular details a priori not specified and unknown. This idea is similar to the ready-to-wear industry, which introduced products, which can be slightly modified later on in contrast to tailor-made creations aiming at maximum accuracy from the beginning. These subsequent corrections can be carried out by machines automatically. This “learning ability” is a key element of machine intelligence.

The past decade confirmed that the view of typical components of the present soft computing as fuzzy logic, neural computing, evolutionary computation and probabilistic reasoning are of complementary nature and that the best results can be applied by their combined application.

Today, the two complementary branches of Machine Intelligence, that is, Artificial Intelligence and Computational Intelligence serve as the basis of Intelligent Engineering Systems. The huge number of scientific results published in Journal and conference proceedings worldwide substantiates this statement. The present book contains several articles taking different viewpoints in the field of intelligent systems.

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