Modeling Multi-Level Systems

This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces t...

Πλήρης περιγραφή

Λεπτομέρειες βιβλιογραφικής εγγραφής
Κύριος συγγραφέας: Iordache, Octavian (Συγγραφέας)
Συγγραφή απο Οργανισμό/Αρχή: SpringerLink (Online service)
Μορφή: Ηλεκτρονική πηγή Ηλ. βιβλίο
Γλώσσα:English
Έκδοση: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
Σειρά:Understanding Complex Systems, 70
Θέματα:
Διαθέσιμο Online:Full Text via HEAL-Link
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245 1 0 |a Modeling Multi-Level Systems  |h [electronic resource] /  |c by Octavian Iordache. 
264 1 |a Berlin, Heidelberg :  |b Springer Berlin Heidelberg,  |c 2011. 
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490 1 |a Understanding Complex Systems,  |x 1860-0832 ;  |v 70 
505 0 |a Introduction -- Methodological Resources -- Conventional PSM frames -- New PSM frames.-Mixing in chemical reactors -- Compartmental systems -- Turbulent mixing -- Entropy -- Formal concept analysis -- Existential graphs -- Evolvable designs of experiments -- Autonomous systems perspective. 
520 |a This book is devoted to modeling of multi-level complex systems, a challenging domain for engineers, researchers and entrepreneurs, confronted with the transition from learning and adaptability to evolvability and autonomy for technologies, devices and problem solving methods. Chapter 1 introduces the multi-scale and multi-level systems and highlights their presence in different domains of science and technology. Methodologies as, random systems, non-Archimedean analysis, category theory and specific techniques as model categorification and integrative closure, are presented in chapter 2. Chapters 3 and 4 describe polystochastic models, PSM, and their developments. Categorical formulation of integrative closure offers the general PSM framework which serves as a flexible guideline for a large variety of multi-level modeling problems. Focusing on chemical engineering, pharmaceutical and environmental case studies, the chapters 5 to 8 analyze mixing, turbulent dispersion and entropy production for multi-scale systems. Taking inspiration from systems sciences, chapters 9 to 11 highlight multi-level modeling potentialities in formal concept analysis, existential graphs and evolvable designs of experiments. Case studies refer to separation flow-sheets, pharmaceutical pipeline, drug design and development, reliability management systems, security and failure analysis. Perspectives and integrative points of view are discussed in chapter 12. Autonomous and viable systems, multi-agents, organic and autonomic computing, multi-level informational systems, are revealed as promising domains for future applications. Written for: engineers, researchers, entrepreneurs and students in chemical, pharmaceutical, environmental and systems sciences engineering, and for applied mathematicians. 
650 0 |a Engineering. 
650 0 |a Statistical physics. 
650 0 |a Computational intelligence. 
650 0 |a Complexity, Computational. 
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650 2 4 |a Nonlinear Dynamics. 
650 2 4 |a Computational Intelligence. 
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776 0 8 |i Printed edition:  |z 9783642179457 
830 0 |a Understanding Complex Systems,  |x 1860-0832 ;  |v 70 
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950 |a Physics and Astronomy (Springer-11651)