Stochastic Dynamics (Over 1,400 results)

Condition: Good. A copy that has been read, but remains in clean condition. All pages are intact, and the cover is intact (including dust cover, if applicable). The spine may show signs of wear. Pages can include limited notes and highlighting, and the copy can include "From the library of" labels or limited small stickers. Book may have a remainder mark or be a price cutter.…

Broschiert. Condition: Gut. 123 Seiten; Das Buch ist ordentlich erhalten und kann altersbedingte Gebrauchsspuren aufweisen. Neben dem oben aufgeführten Aufsatz befinden sich auch weitere Beiträge auch anderer Autoren in dem Werk. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 215.

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Paperback or Softback. Condition: New. Dynamics of Nonlinear Stochastic Systems. Book.

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Condition: good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail.…

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Condition: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

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Condition: Fine. *Price HAS BEEN REDUCED by 10% until Monday, Nov. 2 (weekend sale item)* First edition, first printing, 374 pp., hardcover, previous owner's small inscription to front pastedown else fine. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.…

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Paperback. Condition: Wie neu. 210 S.; Ill. Like new. Shrink wrapped. Sprache: Englisch Gewicht in Gramm: 495.

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Paperback. Condition: New. Buildings, bridges and tunnels are continuously exposed to forces of nature such as wind, waves, earthquakes and even traffic. Because these forces are hard to predict and model, it is also hard to predict how these structures respond. Stochastic Dynamics introduces a way of modeling forces and responses using stochastic systems, providing a method of statistical analysis where precise predictions are impossible. Including topics such as stochastic processes, stochastic vibration theory of linear structures, reliability theory of dynamicstructures and Monte Carlo techniques, this book explains stochastic structural dynamics and how to apply it to modern structures.…

Paperback. Condition: New. Many multiagent dynamics can be modeled as a stochastic process in which the agents in the system change their state over time in interaction with each other. The Gillespie algorithms are popular algorithms that exactly simulate such stochastic multiagent dynamics when each state change is driven by a discrete event, the dynamics is defined in continuous time, and the stochastic law of event occurrence is governed by independent Poisson processes. The first main part of this volume provides a tutorial on the Gillespie algorithms focusing on simulation of social multiagent dynamics occurring in populations and networks. The authors clarify why one should use the continuous-time models and the Gillespie algorithms in many cases, instead of easier-to-understand discrete-time models. The remainder of the Element reviews recent extensions of the Gillespie algorithms aiming to add more reality to the model (i.e., non-Poissonian cases) or to speed up the simulations. This title is also available as open access on Cambridge Core.…

Condition: NEW.

Condition: New.

Hardcover. Condition: Very Good. No Jacket. Former library book; May have limited writing in cover pages. Pages are unmarked. ~ ThriftBooks: Read More, Spend Less.

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Softcover. Condition: Very Good. Dust Jacket Condition: N/A. Undated. x, 276pp, errata sheet loosely enclosed. Pictorial light card covers. 8vo. Light chipping to edges and wear to covers, covers curling. Internally, neat, clean, bright and tight.

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Paperback. Condition: new. Paperback. Research and development organizations operate in environments characterized by technical complexity, uncertainty, limited resources, demanding schedules, and rapidly changing strategic priorities. Their success depends not only on scientific knowledge and engineering capability but also on the ability of multidisciplinary teams to integrate specialized expertise, communicate effectively, manage uncertainty, and make sound decisions. These challenges become particularly significant when projects involve emerging technologies, distributed teams, and objectives that may evolve throughout the development process.This book was written to provide an integrated perspective on the management and performance of multidisciplinary R&D teams and organizations. It brings together concepts from engineering management, organizational behavior, systems thinking, probability, stochastic modeling, computational simulation, and decision science. Its central premise is that uncertainty should not be treated solely as an obstacle. When it is identified, modeled, and interpreted systematically, uncertainty can provide valuable information for planning, resource allocation, risk mitigation, and organizational learning.Particular attention is given to the relationships among individual competence, team cohesion, communication, technical uncertainty, organizational structure, and project performance. These factors do not operate independently. They form an interconnected system in which decisions and behaviors generate feedback that can either strengthen or weaken organizational performance. Accordingly, the book approaches R&D management as a dynamic process requiring continuous observation, evaluation, adaptation, and learning.The book also examines how stochastic models and computational methods can support management decisions. Monte Carlo simulation, sensitivity analysis, network modeling, risk assessment, and related techniques provide a structured means of exploring possible outcomes when complete information is unavailable. These methods do not eliminate uncertainty or replace managerial judgment. Instead, they help decision-makers understand the range of plausible outcomes, identify influential variables, compare alternative strategies, and select actions that are more robust under changing conditions.The material is intended for engineering managers, R&D leaders, project managers, systems engineers, researchers, graduate students, and professionals working in technology-intensive organizations. Readers with management backgrounds may use the book to develop a better understanding of quantitative modeling and simulation. Readers with engineering or scientific backgrounds may use it to examine the organizational and behavioral dimensions of technical performance. The interdisciplinary presentation is designed to encourage communication between these communities and support a more unified approach to R&D management.This book does not propose that a single model can fully represent the complexity of an R&D organization. Human behavior, technical development, and organizational change cannot be predicted with absolute precision. Nevertheless, carefully constructed models can clarify assumptions, reveal dependencies, test alternative scenarios, and improve the quality and transparency of management decisions. Their greatest value lies not in producing a single definitive forecast but in supporting informed reasoning under uncertainty.Ultimately, the book seeks to contribute to the development of R&D organizations that are more collaborative, adaptive, resilient, and capable of sustained innovation. By connecting human and organizational considerations with stochastic modeling and computational analysis, it offers a framework through which uncertainty can be transformed from an unmanaged source o Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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