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03671nam a22004815i 4500 |
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|a 9783642179464
|9 978-3-642-17946-4
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|a 10.1007/978-3-642-17946-4
|2 doi
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|a QA76.9.M35
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|a Iordache, Octavian.
|e author.
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|a Modeling Multi-Level Systems
|h [electronic resource] /
|c by Octavian Iordache.
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264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2011.
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300 |
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|a XV, 232 p.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
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|a text file
|b PDF
|2 rda
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|a Understanding Complex Systems,
|x 1860-0832 ;
|v 70
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|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.
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|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.
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650 |
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|a Engineering.
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650 |
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|a Statistical physics.
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|a Computational intelligence.
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|a Complexity, Computational.
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|a Engineering.
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|a Complexity.
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650 |
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|a Nonlinear Dynamics.
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650 |
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|a Computational Intelligence.
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783642179457
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830 |
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|a Understanding Complex Systems,
|x 1860-0832 ;
|v 70
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856 |
4 |
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|u http://dx.doi.org/10.1007/978-3-642-17946-4
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-PHA
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950 |
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|a Physics and Astronomy (Springer-11651)
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