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Octavian Iordache's Modeling Multi-Level Systems PDF

By Octavian Iordache

ISBN-10: 3642179452

ISBN-13: 9783642179457

This ebook is dedicated to modeling of multi-level advanced platforms, a hard area for engineers, researchers and marketers, faced with the transition from studying and flexibility to evolvability and autonomy for applied sciences, units and challenge fixing equipment. bankruptcy 1 introduces the multi-scale and multi-level platforms and highlights their presence in several domain names of technological know-how and know-how. Methodologies as, random platforms, non-Archimedean research, classification concept and particular concepts as version categorification and integrative closure, are provided in bankruptcy 2. Chapters three and four describe polystochastic types, PSM, and their advancements. specific formula of integrative closure deals the final PSM framework which serves as a versatile guide for a wide number of multi-level modeling problems.

Focusing on chemical engineering, pharmaceutical and environmental case reviews, the chapters five to eight research blending, turbulent dispersion and entropy construction for multi-scale platforms. Taking notion from platforms sciences, chapters nine to eleven spotlight multi-level modeling prospects in formal idea research, existential graphs and evolvable designs of experiments. Case stories seek advice from separation flow-sheets, pharmaceutical pipeline, drug layout and improvement, reliability administration platforms, defense and failure research. views and integrative issues of view are mentioned in bankruptcy 12. self sufficient and possible platforms, multi-agents, natural and autonomic computing, multi-level informational platforms, are printed as promising domain names for destiny applications.

Written for: engineers, researchers, marketers and scholars in chemical, pharmaceutical, environmental and platforms sciences engineering, and for utilized mathematicians.

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Additional resources for Modeling Multi-Level Systems

Sample text

Despite the success of Cantor in constructing the continuum from arithmetical materials, a number of mathematicians of the late 19th and early 20th centuries remained opposed, in varying degrees, to the idea of explicating the continuum concept entirely in discrete terms. These include Peirce, Veronese, Poincaré, and Brouwer. Studies of interest for multi-level modeling are the geometry of Veronese (1891) and the p-adic number theory due to Hensel (1905). In physics, chemistry, engineering as in other domains, the real field R and the complex field C play the main roles.

1 Introducing Category Theory Elements of mathematical category theory are presented here in an informal way. MacLane (1971) monograph is the reference for the formal approach (Appendix 2). The benefits of category theory, CT, are rooted in the possibility to apply all its powerful constructions and methods to the specific problem if this is formulated in the categorical frame. There exist strong arguments in favor of utilizing category theory as foundation for cognitive sciences and modeling (Goguen 1991, MacNamara and Reyes 1994).

Tetradic architectures are endorsed by arguments from informatics, higher category, neurodynamics and semiotics. 1 Random Systems One of the main features of complex systems is their randomness. Basic notions concerning “random systems”, RS, and their utility for PSM will be presented in this section. The so-called Markovian dependence characterizes the evolution of systems with memory restricted to the last step. Consequently Markovian models describe linear systems and cannot describe complex processes characterized by selflearning, hysteresis, instability to initial conditions and chaotic behaviors.

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Modeling Multi-Level Systems by Octavian Iordache


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