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03349nam a22005295i 4500 |
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978-3-642-10654-5 |
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DE-He213 |
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20151103124224.0 |
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cr nn 008mamaa |
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100319s2010 gw | s |||| 0|eng d |
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|a 9783642106545
|9 978-3-642-10654-5
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|a 10.1007/978-3-642-10654-5
|2 doi
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|a Iordache, Octavian.
|e author.
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|a Polystochastic Models for Complexity
|h [electronic resource] /
|c by Octavian Iordache.
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| 264 |
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|a Berlin, Heidelberg :
|b Springer Berlin Heidelberg,
|c 2010.
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| 300 |
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|a XX, 298 p. 94 illus.
|b online resource.
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
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|a online resource
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|a text file
|b PDF
|2 rda
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| 490 |
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|a Understanding Complex Systems,
|x 1860-0832
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| 505 |
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|a Methods -- Physical and Chemical Systems -- Biosystems and Bioinspired Systems -- Systems Sciences and Cognitive Systems -- Perspectives -- Appendices.
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|a This book is devoted to complexity understanding and management, considered as the main source of efficiency and prosperity for the next decades. Divided into six chapters, the book begins with a presentation of basic concepts as complexity, emergence and closure. The second chapter looks to methods and introduces polystochastic models, the wave equation, possibilities and entropy. The third chapter focusing on physical and chemical systems analyzes flow-sheet synthesis, cyclic operations of separation, drug delivery systems and entropy production. Biomimetic systems represent the main objective of the fourth chapter. Case studies refer to bio-inspired calculation methods, to the role of artificial genetic codes, neural networks and neural codes for evolutionary calculus and for evolvable circuits as biomimetic devices. The fifth chapter, taking its inspiration from systems sciences and cognitive sciences looks to engineering design, case base reasoning methods, failure analysis, and multi-agent manufacturing systems. Perspectives and integrative points of view are discussed in the sixth chapter with reference to the classification of sciences, cybernetics and its extensions, and to transdisciplinarity and categorification. Written for: engineers, researchers, and students in chemical, biochemical, computing and systems science engineering, in neuroscience, psychology, philosophy and mathematics.
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|a Engineering.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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|a Dynamics.
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| 650 |
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|a Ergodic theory.
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| 650 |
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|a Statistical physics.
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| 650 |
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|a Dynamical systems.
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| 650 |
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|a Complexity, Computational.
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4 |
|a Engineering.
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| 650 |
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|a Complexity.
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| 650 |
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|a Statistical Physics, Dynamical Systems and Complexity.
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| 650 |
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4 |
|a Artificial Intelligence (incl. Robotics).
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| 650 |
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|a Dynamical Systems and Ergodic Theory.
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| 710 |
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|a SpringerLink (Online service)
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|t Springer eBooks
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|i Printed edition:
|z 9783642106538
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| 830 |
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|a Understanding Complex Systems,
|x 1860-0832
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| 856 |
4 |
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|u http://dx.doi.org/10.1007/978-3-642-10654-5
|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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