Connectez-vous avec Facebook:
S'inscrire
Mot de passe oublié?
Historique de recherche
Liste pense-bête
Liens vers eurolivre.fr
Detailseite wird geladen...
ISBN: 9781849965279
[ED: Buch], [PU: Springer], Neuware - Robust control mechanisms customarily require knowledge of the system's describing equations which may be of the high order differential type. In order to produce these equations, mathematical models can often be derived and correlated with measured dynamic behavior. There are two flaws in this approach one is the level of inexactness introduced by linearizations and the other when no model is apparent. Several years ago a new genre of control systems came to light that are much less dependent on differential models such as fuzzy logic and genetic algorithms. Both of these soft computing solutions require quite considerable a priori system knowledge to create a control scheme and sometimes complicated training program before they can be implemented in a real world dynamic system. Michie and Chambers' BOXES methodology created a black box system that was designed to control a mechanically unstable system with very little a priori system knowledge, linearization or approximation. All the method needed was some notion of maximum and minimum values for the state variables and a set of boundaries that divided each variable into an integer state number. The BOXES Methodology applies the method to a variety of systems including continuous and chaotic dynamic systems, and discusses how it may be possible to create a generic control method that is self organizing and adaptive that learns with the assistance of near neighbouring states. The BOXES Methodology introduces students at the undergraduate and master's level to black box dynamic system control , and gives lecturers access to background materials that can be used in their courses in support of student research and classroom presentations in novel control systems and real-time applications of artificial intelligence. Designers are provided with a novel method of optimization and controller design when the equations of a system are difficult or unknown. Researchers interested in artificial intelligence (AI) research and models of the brain and practitioners from other areas of biology and technology are given an insight into how AI software can be written and adapted to operate in real-time. -, [SC: 0.00], Neuware, gewerbliches Angebot, 235x155x19 mm, [GW: 537g]
Booklooker.de |
ISBN: 9781849965279
[ED: Buch], [PU: Springer], Neuware - Robust control mechanisms customarily require knowledge of the system's describing equations which may be of the high order differential type. In order to produce these equations, mathematical models can often be derived and correlated with measured dynamic behavior. There are two flaws in this approach one is the level of inexactness introduced by linearizations and the other when no model is apparent. Several years ago a new genre of control systems came to light that are much less dependent on differential models such as fuzzy logic and genetic algorithms. Both of these soft computing solutions require quite considerable a priori system knowledge to create a control scheme and sometimes complicated training program before they can be implemented in a real world dynamic system. Michie and Chambers' BOXES methodology created a black box system that was designed to control a mechanically unstable system with very little a priori system knowledge, linearization or approximation. All the method needed was some notion of maximum and minimum values for the state variables and a set of boundaries that divided each variable into an integer state number. The BOXES Methodology applies the method to a variety of systems including continuous and chaotic dynamic systems, and discusses how it may be possible to create a generic control method that is self organizing and adaptive that learns with the assistance of near neighbouring states. The BOXES Methodology introduces students at the undergraduate and master's level to black box dynamic system control , and gives lecturers access to background materials that can be used in their courses in support of student research and classroom presentations in novel control systems and real-time applications of artificial intelligence. Designers are provided with a novel method of optimization and controller design when the equations of a syste, [SC: 0.00], Neuware, gewerbliches Angebot, 235x155x19 mm, [GW: 537g]
Booklooker.de |
ISBN: 9781849965279
[ED: Buch], [PU: Springer], Neuware - Robust control mechanisms customarily require knowledge of the system's describing equations which may be of the high order differential type. In order to produce these equations, mathematical models can often be derived and correlated with measured dynamic behavior. There are two flaws in this approach one is the level of inexactness introduced by linearizations and the other when no model is apparent. Several years ago a new genre of control systems came to light that are much less dependent on differential models such as fuzzy logic and genetic algorithms. Both of these soft computing solutions require quite considerable a priori system knowledge to create a control scheme and sometimes complicated training program before they can be implemented in a real world dynamic system. Michie and Chambers' BOXES methodology created a black box system that was designed to control a mechanically unstable system with very little a priori system knowledge, linearization or approximation. All the method needed was some notion of maximum and minimum values for the state variables and a set of boundaries that divided each variable into an integer state number. The BOXES Methodology applies the method to a variety of systems including continuous and chaotic dynamic systems, and discusses how it may be possible to create a generic control method that is self organizing and adaptive that learns with the assistance of near neighbouring states. The BOXES Methodology introduces students at the undergraduate and master's level to black box dynamic system control , and gives lecturers access to background materials that can be used in their courses in support of student research and classroom presentations in novel control systems and real-time applications of artificial intelligence. Designers are provided with a novel method of optimization and controller design when the equations of a syste, [SC: 0.00], Neuware, gewerbliches Angebot, 235x155x19 mm, [GW: 537g]
Booklooker.de |
ISBN: 9781849965279
[ED: Buch], [PU: Springer], Neuware - Robust control mechanisms customarily require knowledge of the system's describing equations which may be of the high order differential type. In order to produce these equations, mathematical models can often be derived and correlated with measured dynamic behavior. There are two flaws in this approach one is the level of inexactness introduced by linearizations and the other when no model is apparent. Several years ago a new genre of control systems came to light that are much less dependent on differential models such as fuzzy logic and genetic algorithms. Both of these soft computing solutions require quite considerable a priori system knowledge to create a control scheme and sometimes complicated training program before they can be implemented in a real world dynamic system. Michie and Chambers' BOXES methodology created a black box system that was designed to control a mechanically unstable system with very little a priori system knowledge, linearization or approximation. All the method needed was some notion of maximum and minimum values for the state variables and a set of boundaries that divided each variable into an integer state number. The BOXES Methodology applies the method to a variety of systems including continuous and chaotic dynamic systems, and discusses how it may be possible to create a generic control method that is self organizing and adaptive that learns with the assistance of near neighbouring states. The BOXES Methodology introduces students at the undergraduate and master's level to black box dynamic system control , and gives lecturers access to background materials that can be used in their courses in support of student research and classroom presentations in novel control systems and real-time applications of artificial intelligence. Designers are provided with a novel method of optimization and controller design when the equations of a syste, [SC: 0.00], Neuware, gewerbliches Angebot, FixedPrice, [GW: 537g]
Booklooker.de |
2012, ISBN: 1849965277
ID: A10036615
2012 Gebundene Ausgabe Algorithmus, Intelligenz / Künstliche Intelligenz, KI, Künstliche Intelligenz - AI, AI ( Künstliche Intelligenz ), Messtechnik, Schwingbewegung - Schwingungslehre ( Schwingung (physikalisch) ), Schwingungslehre ( Schwingung (physikalisch) - Schwingbewegung ), Schwingung (physikalisch) - Schwingbewegung - Schwingungslehre, Systemtheorie, mit Schutzumschlag neu, [PU:Springer]
Achtung-Buecher.de
REDIVIVUS Buchhandlung Hanausch Reinhard, 93053 Regensburg
Frais d'envoiVersandkostenfrei innerhalb der BRD (EUR 0.00) Details... |
Auteur: | |
Titre: | The BOXES Methodology: Black Box Dynamic Control |
ISBN: | 9781849965279 |
Informations détaillées sur le livre - The BOXES Methodology: Black Box Dynamic Control
EAN (ISBN-13): 9781849965279
ISBN (ISBN-10): 1849965277
Version reliée
Date de parution: 2012
Editeur: Springer-Verlag GmbH
224 Pages
Poids: 0,500 kg
Langue: Englisch
Livre dans la base de données depuis 28.03.2009 05:54:26
Livre trouvé récemment le 30.12.2016 15:41:40
ISBN/EAN: 9781849965279
ISBN - Autres types d'écriture:
1-84996-527-7, 978-1-84996-527-9
< pour archiver...
Adjacent Livres
- "Rapid Modelling and Quick Response" (9781849965262)
- "The BOXES Methodology", de "David W. Russell" (9781849965286)
- "Rapid Modelling and Quick Response - Intersection of Theory and Practice", de "9781846281341" (9781849965255)
- "Rapid Modelling and Quick Response", de "Gerald Reiner" (9781849965248)
- "One-of-a-Kind Production", de "Yiliu Tu" (9781849965309)
- "One-of-a-Kind Production", de "9781849965316" (9781849965316)