Zurück zur Startseite
|Eingestellt in Kategorie:

Bild 1 von 2

Einführung in die stochastische Suche und..., James C Spall - Bild 1 von 2
Einführung in die stochastische Suche und..., James C Spall - Bild 2 von 2
Ähnlichen Artikel verkaufen?
Selbst verkaufen

Einführung in die stochastische Suche und..., James C Spall

worldofbooksinc
(235867)
Angemeldet als gewerblicher Verkäufer
Mehr Artikel des Verkäufers
Verkäufer kontaktieren
US $50,99
Ca.CHF 41,18
Artikelzustand:
Gut
Ganz entspannt. Kostenloser Versand & Rückversand.
Versand:
Kostenlos USPS Media MailTM.
Standort: Montgomery Illinois, USA
Lieferung:
Lieferung zwischen Fr, 8. Aug und Di, 12. Aug nach 94104 bei heutigem Zahlungseingang
Wir wenden ein spezielles Verfahren zur Einschätzung des Liefertermins an – in diese Schätzung fließen Faktoren wie die Entfernung des Käufers zum Artikelstandort, der gewählte Versandservice, die bisher versandten Artikel des Verkäufers und weitere ein. Insbesondere während saisonaler Spitzenzeiten können die Lieferzeiten abweichen.
Rücknahme:
30 Tage Rückgabe. Verkäufer zahlt Rückversand.
Zahlungen:
     Diners Club

Sicher einkaufen

eBay-Käuferschutz
Geld zurück, wenn etwas mit diesem Artikel nicht stimmt. Mehr erfahreneBay-Käuferschutz - wird in neuem Fenster oder Tab geöffnet
Der Verkäufer ist für dieses Angebot verantwortlich.
eBay-Artikelnr.:354621078028
Zuletzt aktualisiert am 14. Jun. 2025 10:15:47 MESZAlle Änderungen ansehenAlle Änderungen ansehen

Artikelmerkmale

Artikelzustand
Gut: Buch, das gelesen wurde, sich aber in einem guten Zustand befindet. Der Einband weist nur sehr ...
Book Title
Introduction to Stochastic Search and Optimization: Estimation...
ISBN
0471330523
EAN
9780471330523
Date of Publication
20030425
Release Title
Introduction to Stochastic Search and Optimization: Estimation...
Artist
James C Spall
Brand
N/A
Colour
N/A

Über dieses Produkt

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0471330523
ISBN-13
9780471330523
eBay Product ID (ePID)
499132

Product Key Features

Number of Pages
618 Pages
Publication Name
Introduction to Stochastic Search and Optimization : Estimation, Simulation, and Control
Language
English
Publication Year
2003
Subject
Probability & Statistics / Stochastic Processes, Applied, Optimization
Type
Textbook
Author
James C. Spall
Subject Area
Mathematics
Series
Wiley Series in Discrete Mathematics and Optimization Ser.
Format
Hardcover

Dimensions

Item Height
1.4 in
Item Weight
43.6 Oz
Item Length
10.2 in
Item Width
7.3 in

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2002-038049
Dewey Edition
21
Reviews
"This volume deserves a prominent role not only as a textbook, but also as a desk reference for anyone who must cope with noisy data..." ( Computing Reviews.com , January 6, 2006) "...well written and accessible to a wide audience...a welcome addition to the control and optimization community." ( IEEE Control Systems Magazine , June 2005) "...a step toward learning more about optimization techniques that often are not part of a statistician's training." ( Journal of the American Statistical Association , December 2004) "...provides easy access to a very broad, but related, collection of topics..." ( Short Book Reviews , August 2004) "Rather than simply present various stochastic search and optimization algorithms as a collection of distinct techniques, the book compares and contrasts the algorithms within a broader context of stochastic methods." ( Technometrics , August 2004, Vol. 46, No. 3)
Series Volume Number
64
Illustrated
Yes
Dewey Decimal
519.2
Table Of Content
Preface. Stochastic Search and Optimization: Motivation and Supporting Results. Direct Methods for Stochastic Search. Recursive Estimation for Linear Models. Stochastic Approximation for Nonlinear Root-Finding. Stochastic Gradient Form of Stochastic Approximation. Stochastic Approximation and the Finite-Difference Method. Simultaneous Perturbation Stochastic Approximation. Annealing-Type Algorithms. Evolutionary Computation I: Genetic Algorithms. Evolutionary Computation II: General Methods and Theory. Reinforcement Learning via Temporal Differences. Statistical Methods for Optimization in Discrete Problems. Model Selection and Statistical Information. Simulation-Based Optimization I: Regeneration, Common Random Numbers, and Selection Methods. Simulation-Based Optimization II: Stochastic Gradient and Sample Path Methods. Markov Chain Monte Carlo. Optimal Design for Experimental Inputs. Appendix A. Selected Results from Multivariate Analysis. Appendix B. Some Basic Tests in Statistics. Appendix C. Probability Theory and Convergence. Appendix D. Random Number Generation. Appendix E. Markov Processes. Answers to Selected Exercises. References. Frequently Used Notation. Index.
Synopsis
A unique interdisciplinary foundation for real-world problem solving Stochastic search and optimization techniques are used in a vast number of areas, including aerospace, medicine, transportation, and finance, to name but a few. Whether the goal is refining the design of a missile or aircraft, determining the effectiveness of a new drug, developing the most efficient timing strategies for traffic signals, or making investment decisions in order to increase profits, stochastic algorithms can help researchers and practitioners devise optimal solutions to countless real-world problems. Introduction to Stochastic Search and Optimization: Estimation, Simulation, and Control is a graduate-level introduction to the principles, algorithms, and practical aspects of stochastic optimization, including applications drawn from engineering, statistics, and computer science. The treatment is both rigorous and broadly accessible, distinguishing this text from much of the current literature and providing students, researchers, and practitioners with a strong foundation for the often-daunting task of solving real-world problems. The text covers a broad range of today's most widely used stochastic algorithms, including: Random search Recursive linear estimation Stochastic approximation Simulated annealing Genetic and evolutionary methods Machine (reinforcement) learning Model selection Simulation-based optimization Markov chain Monte Carlo Optimal experimental design The book includes over 130 examples, Web links to software and data sets, more than 250 exercises for the reader, and an extensive list of references. These features help make the text an invaluable resource for those interested in the theory or practice of stochastic search and optimization., * Unique in its survey of the range of topics. * Contains a strong, interdisciplinary format that will appeal to both students and researchers. * Features exercises and web links to software and data sets., A unique interdisciplinary foundation for real-world problem solving Stochastic search and optimization techniques are used in a vast number of areas, including aerospace, medicine, transportation, and finance, to name but a few.
LC Classification Number
QA274.S63 2003

Artikelbeschreibung des Verkäufers

Info zu diesem Verkäufer

worldofbooksinc

97,7% positive Bewertungen•1.2 Mio. Artikel verkauft

Mitglied seit Feb 2020
Antwortet meist innerhalb 24 Stunden
Angemeldet als gewerblicher Verkäufer
In 2002, World of Books Group was founded on an ethos to do good, protect the planet and support charities by enabling more goods to be reused. Since then, we've grown into to a global company ...
Mehr anzeigen
Shop besuchenKontakt

Detaillierte Verkäuferbewertungen

Durchschnitt in den letzten 12 Monaten
Genaue Beschreibung
4.8
Angemessene Versandkosten
5.0
Lieferzeit
5.0
Kommunikation
5.0

Verkäuferbewertungen (272'046)

Alle Bewertungen
Positiv
Neutral
Negativ
Alle Bewertungen ansehen

Noch mehr entdecken: