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Input Modeling with Phase-Type Distributions and Markov Models : Theory and Applications - Peter Buchholz
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Input Modeling with Phase-Type Distributions and Markov Models : Theory and Applications - Livres de poche

2014, ISBN: 3319066730

[EAN: 9783319066738], Neubuch, [SC: 0.0], [PU: Springer International Publishing], INPUTMODELING; MARKOVMODELS; MARKOVIANARRIVALPROCESSES; PHASETYPEDISTRIBUTIONS; STOCHASTICSIMULATION, Dr… Plus…

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ISBN: 9783319066738

Containing a summary of several recent results on Markov-based input modeling in a coherent notation, this book introduces and compares algorithms for parameter fitting and gives an overv… Plus…

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Input Modeling with Phase-Type Distributions and Markov Models: Theory and Applications (SpringerBriefs in Mathematics) - Buchholz, Peter
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Input Modeling with Phase-Type Distributions and Markov Models: Theory and Applications (SpringerBriefs in Mathematics) - Livres de poche

2014

ISBN: 9783319066738

Mitwirkende: Kriege, Jan, Mitwirkende: Felko, Iryna, Springer, Taschenbuch, Auflage: 2014, 140 Seiten, Publiziert: 2014-06-06T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 7 black & whi… Plus…

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Input Modeling with Phase-Type Distributions and Markov Models: Theory and Applications (SpringerBriefs in Mathematics) - Livres de poche

2014, ISBN: 9783319066738

Mitwirkende: Kriege, Jan, Mitwirkende: Felko, Iryna, Springer, Taschenbuch, Auflage: 2014, 140 Seiten, Publiziert: 2014-06-06T00:00:01Z, Produktgruppe: Buch, Hersteller-Nr.: 7 black & whi… Plus…

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Buchholz, Peter, Kriege, Jan, Felko, Iryna:
Input Modeling with Phase-Type Distributions and Markov Models: Theory and Applications (SpringerBriefs in Mathematics) - Livres de poche

2014, ISBN: 9783319066738

Springer, Paperback, Auflage: 2014, 139 Seiten, Publiziert: 2014-06-06T00:00:01Z, Produktgruppe: Book, Hersteller-Nr.: 7 black & white illustrations, 35 colour, 2.49 kg, Books Global Stor… Plus…

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Input Modeling with Phase-Type Distributions and Markov Models: Theory and Applications Peter Buchholz Author

Containing a summary of several recent results on Markov-based input modeling in a coherent notation, this book introduces and compares algorithms for parameter fitting and gives an overview of available software tools in the area. Due to progress made in recent years with respect to new algorithms to generate PH distributions and Markovian arrival processes from measured data, the models outlined are useful alternatives to other distributions or stochastic processes used for input modeling. Graduate students and researchers in applied probability, operations research and computer science along with practitioners using simulation or analytical models for performance analysis and capacity planning will find the unified notation and up-to-date results presented useful. Input modeling is the key step in model based system analysis to adequately describe the load of a system using stochastic models. The goal of input modeling is to find a stochastic model to describe a sequence of measurements from a real system to model for example the inter-arrival times of packets in a computer network or failure times of components in a manufacturing plant. Typical application areas are performance and dependability analysis of computer systems, communication networks, logistics or manufacturing systems but also the analysis of biological or chemical reaction networks and similar problems. Often the measured values have a high variability and are correlated. It's been known for a long time that Markov based models like phase type distributions or Markovian arrival processes are very general and allow one to capture even complex behaviors. However, the parameterization of these models results often in a complex and non-linear optimization problem. Only recently, several new results about the modeling capabilities of Markov based models and algorithms to fit the parameters of those models have been published.

Informations détaillées sur le livre - Input Modeling with Phase-Type Distributions and Markov Models: Theory and Applications Peter Buchholz Author


EAN (ISBN-13): 9783319066738
ISBN (ISBN-10): 3319066730
Version reliée
Livre de poche
Date de parution: 2014
Editeur: Springer International Publishing Core >1

Livre dans la base de données depuis 2014-05-26T13:32:37+02:00 (Zurich)
Page de détail modifiée en dernier sur 2024-04-03T16:50:13+02:00 (Zurich)
ISBN/EAN: 9783319066738

ISBN - Autres types d'écriture:
3-319-06673-0, 978-3-319-06673-8
Autres types d'écriture et termes associés:
Auteur du livre: peter krieg, peter buchholz, kriege, jan buchholz
Titre du livre: type, phase theory, markov, marko, jan, kriege, applications the theory distributions, typ, peter buchholz


Données de l'éditeur

Auteur: Peter Buchholz; Jan Kriege; Iryna Felko
Titre: SpringerBriefs in Mathematics; Input Modeling with Phase-Type Distributions and Markov Models - Theory and Applications
Editeur: Springer; Springer International Publishing
127 Pages
Date de parution: 2014-06-06
Cham; CH
Imprimé / Fabriqué en
Langue: Anglais
53,49 € (DE)
54,99 € (AT)
59,00 CHF (CH)
POD
XII, 127 p. 42 illus., 35 illus. in color.

BC; Hardcover, Softcover / Mathematik/Wahrscheinlichkeitstheorie, Stochastik, Mathematische Statistik; Wahrscheinlichkeitsrechnung und Statistik; Verstehen; Input modeling; Markov models; Markovian arrival processes; phase type distributions; stochastic simulation; Probability Theory; Mathematical Modeling and Industrial Mathematics; Mathematical Software; Mathematical Applications in Computer Science; Stochastik; Mathematische Modellierung; Mathematik für Ingenieure; Mathematische und statistische Software; Theoretische Informatik; EA

1. Introduction.- 2. Phase Type Distributions.- 3. Parameter Fitting for Phase Type Distributions.- 4. Markovian Arrival Processes.- 5. Parameter Fitting of MAPs.- 6. Stochastic Models including PH Distributions and MAPs.- 7. Software Tools.- 8. Conclusion.- References.- Index.
Contains an overview of available open source software tools for parameter fitting of PH distributions and MAPs Presents a large number of algorithms to fit the parameters of PH distributions or MAPs according to measured traces Introduces the use of PH distributions and MAPs in stochastic models including simulation models, especially in the network simulator OMNeT++ Includes supplementary material: sn.pub/extras

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