Ermoliev (57 results)

gebundene Ausgabe. Condition: Gut. 571 Seiten; Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich neben dem Rückenschild lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 1010.…

Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

paperback. Condition: Good. Ex- library book with stamps/ stickers.

Condition: Used. pp. 348.

Condition: Used. pp. 348 49:B&W 6.14 x 9.21 in or 234 x 156 mm (Royal 8vo) Perfect Bound on White w/Gloss Lam.

Condition: Used. pp. 348.

Hardcover. Condition: Sehr gut. Berlin, Springer (1988). gr.8°. 62 figs. XIII, 571 p. Hardbound. (back slightly faded, otherwise in very good condition).- Springer Series in Computational Mathematics, 10.

PF. Condition: New.

Condition: New. In English.

Soft cover. Condition: As New. Like new, never been used.

Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.

Condition: New. pp. 600.

Soft Cover. Condition: Good. Ex-library with the usual features. The interior is clean and tight. Binding is good. Cover shows light wear and has library label on the spine. 336 pages. Ex-Library.

Condition: Like New. Used - Like New. Book is new and unread but may have minor shelf wear. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions.…

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Rapid changes in today's environment emphasize the need for models and meth ods capable of dealing with the uncertainty inherent in virtually all systems re lated to economics, meteorology, demography, ecology, etc. Systems involving interactions between man, nature and technology are subject to disturbances which may be unlike anything which has been experienced in the past. In the technological revolution increases uncertainty-as each new stage particular, perturbs existing knowledge of structures, limitations and constraints. At the same time, many systems are often too complex to allow for precise measure ment of the parameters or the state of the system. Uncertainty, nonstationarity, disequilibrium are pervasivE' characteristics of most modern systems. In order to manage such situations (or to survive in such an environment) we must develop systems which can facilitate oar response to uncertainty and changing conditions. In our individual behavior we often follow guidelines that are conditioned by the need to be prepared for all (likely) eventualities: insur ance, wearing seat belts, savings versus investments, annual medical check.ups, even keeping an umbrella at the office, etc. One can identify two major types of mechanisms: the short term adaptive adjustments (defensive driving, mar keting, inventory control, etc.) that are made after making some observations of the system's parameters, and the long term anticipative actions (engineer ing design, policy setting, allocation of resources, investment strategies, etc.). …

Condition: New.

Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: Sehr gut. Zustand: Sehr gut | Seiten: 586 | Sprache: Englisch | Produktart: Bücher | Keine Beschreibung verfügbar.

Condition: New. In English.

Condition: New. In English.

Condition: New. In English.

Condition: New. In English.

Hard cover. Condition: Good. No jacket. Spine sunned, as are narrow portions of covers adjacent to spine. One sticker from previous owner on inside front cover, otherwise unmarked and near fine.

Paperback. Condition: New. 2010 ed. Support for addressing the on-going global changes needs solutions for new scientific problems which in turn require new concepts and tools. A key issue concerns a vast variety of irreducible uncertainties, including extreme events of high multidimensional consequences, e.g., the climate change. The dilemma is concerned with enormous costs versus massive uncertainties of extreme impacts. Traditional scientific approaches rely on real observations and experiments. Yet no sufficient observations exist for new problems, and "pure" experiments, and learning by doing may be expensive, dangerous, or impossible. In addition, the available historical observations are often contaminated by past actions, and policies. Thus, tools are presented for the explicit treatment of uncertainties using "synthetic" information composed of available "hard" data from historical observations, the results of possible experiments, and scientific facts, as well as "soft" data from experts' opinions, and scenarios.…

Condition: Gut. Zustand: Gut | Seiten: 348 | Sprache: Englisch | Produktart: Bücher | Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic­ itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec­ tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci­ sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu­ tions. Objective and constraint functions of dynamic stochastic optimization problems have the form of multidimensional integrals of rather involved in­ that may have a nonsmooth and even discontinuous character - the tegrands typical situation for "hit-or-miss" type of decision making problems involving irreversibility ofdecisions or/and abrupt changes ofthe system. In general, the exact evaluation of such functions (as is assumed in the standard optimization and control theory) is practically impossible. Also, the problem does not often possess the separability properties that allow to derive the standard in control theory recursive (Bellman) equations.…

Condition: New. pp. 348.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Ongoing global changes bring fundamentally new scientific problems requiring new concepts and tools. A key issue concerns a vast variety of practically irreducible uncertainties, which challenge our traditional models and require new concepts and analytical tools. The uncertainty critically dominantes, e.g., the climate change debates. In short, the dilemma is concerned with enormous costs vs. massive uncertainties of potential extreme impacts. Traditional scientific approaches usually rely on real observations and experiments. Yet no sufficient observations exist for new problems, and 'pure' experiments and learning by doing may be very expensive, dangerous, or simply impossible. In addition, available historical observations are contaminated by actions, policies. The complexity of new problems does not allow to achieve enough certainty by increasing the resolution of models or by bringing in more links. Hence, new tools for modeling and management of uncertainty are needed, as given in this book.…

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Managing safety of diverse systems requires decision-making under uncertainties and risks. Such systems are typically characterized by spatio-temporal heterogeneities, inter-dependencies, externalities, endogenous risks, discontinuities, irreversibility, practically irreducible uncertainties, and rare events with catastrophic consequences. Traditional scientific approaches rely on data from real observations and experiments; yet no sufficient observations exist for new problems, and experiments are usually impossible. Therefore, science-based support for addressing such new class of problems needs to replace the traditional 'deterministic predictions' analysis by new methods and tools for designing decisions that are robust against the involved uncertainties and risks. The new methods treat uncertainties explicitly by using 'synthetic' information derived by integration of 'hard' elements, including available data, results of possible experiments, and formal representations of scientific facts, with 'soft' elements based on diverse representations of scenarios and opinions of public, stakeholders, and experts. The volume presents such effective new methods, and illustrates their applications in different problem areas, including engineering, economy, finance, agriculture, environment, and policy making.…

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective and constraint functions of dynamic stochastic optimization problems have the form of multidimensional integrals of rather involved in that may have a nonsmooth and even discontinuous character - the tegrands typical situation for 'hit-or-miss' type of decision making problems involving irreversibility ofdecisions or/and abrupt changes ofthe system. In general, the exact evaluation of such functions (as is assumed in the standard optimization and control theory) is practically impossible. Also, the problem does not often possess the separability properties that allow to derive the standard in control theory recursive (Bellman) equations.…