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Coping with Uncertainty: Robust Solutions 2010 ed. [Pehme köide]

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  • Formaat: Paperback / softback, 277 pages, kõrgus x laius: 235x155 mm, kaal: 920 g, XVI, 277 p., 1 Paperback / softback
  • Sari: Lecture Notes in Economics and Mathematical Systems 633
  • Ilmumisaeg: 07-Dec-2009
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642037348
  • ISBN-13: 9783642037344
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  • Formaat: Paperback / softback, 277 pages, kõrgus x laius: 235x155 mm, kaal: 920 g, XVI, 277 p., 1 Paperback / softback
  • Sari: Lecture Notes in Economics and Mathematical Systems 633
  • Ilmumisaeg: 07-Dec-2009
  • Kirjastus: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
  • ISBN-10: 3642037348
  • ISBN-13: 9783642037344
Teised raamatud teemal:

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.



This volume presents tools for the treatment of uncertainties using synthetic information composed of available hard data from historical observations, the results of experiments and scientific facts, as well as soft data from expert opinion and scenarios.

General Remarks on Robust Solutions
1(10)
Y. Ermoliev
M. Makowski
K. Marti
References
7(4)
Part I Modeling of Uncertainty and Probabilistic Issues
On Joint Modelling of Random Uncertainty and Fuzzy Imprecision
11(28)
Olgierd Hryniewicz
Introduction
11(2)
Generalizations of Classical Probability and Their Applications in Decision Making
13(9)
Measures of Uncertainty and Criteria of Their Evaluation
13(2)
Probability
15(2)
Dempster-Shafer Theory of Evidence and Possibility Theory
17(3)
Imprecise Probabilities and Their Generalizations
20(2)
Fuzzy Random Variables and Fuzzy Statistics
22(7)
Applications of Fuzzy Statistics in Systems Analysis
29(4)
Verification of the Kyoto Protocol
29(2)
Sequential Testing of a Hypothesis About the Mean Value in the Normal Distribution
31(2)
Conclusions
33(2)
References
35(4)
On the Approximation of a Discrete Multivariate Probability Distribution Using the New Concept of t-Cherry Junction Tree
39(20)
Edith Kovacs
Tamas Szantai
Introduction
39(1)
Preliminaries
40(3)
Notations
40(1)
Cherry Tree and t-Cherry Tree
41(1)
Junction Tree
42(1)
t-Cherry-Junction Tree
43(7)
Construction of a t-Cherry-Junction Tree
43(1)
The Approximation of the Joint Distribution Over X by the Distribution Associated to a t-Cherry-Junction Tree
44(3)
The Relation Between the Approximations Associated to the First-Order Dependence Tree and t-Cherry-Junction Tree
47(3)
Some Practical Results of Our Approximation and Discussions
50(6)
References
56(3)
Part II Robust Solutions Under Uncertainty
Induced Discounting and Risk Management
59(20)
T. Ermolieva
Y. Ermoliev
G. Fischer
M. Makowski
Introduction
59(3)
Standard and Stopping Time Induced Discounting
62(3)
Time Declining Discount Rates
65(3)
Endogenous Discounting
68(3)
Dynamic Risk Profiles and CVaR Risk Measure
71(2)
Intertemporal Inconsistency
73(2)
Concluding Remarks
75(1)
References
76(3)
Cost Effective and Environmentally Safe Emission Trading Under Uncertainty
79(22)
T. Ermolieva
Y. Ermoliev
G. Fischer
M. Jonas
M. Makowski
Introduction
79(3)
Uncertainties and Trends of Carbon Fluxes
82(2)
Detectability of Emission Changes
84(2)
Trade Equilibrium Under Uncertainty
86(4)
Dynamic Bilateral Trading Processes
90(2)
Computerized Multi-agent Decentralized Trading System
92(1)
Myopic Market Processes
93(3)
Concluding Remarks
96(1)
References
97(4)
Robust Design of Networks Under Risks
101(40)
Y. Ermoliev
A. Gaivoronski
M. Makowski
Introduction
101(3)
Cooperative Provision of Advanced Mobile Data Services
104(2)
Simplified Model of the Service Portfolio
106(7)
Description of Services
106(2)
Profit Model of an Actor
108(2)
Service Portfolio: Financial Perspective
110(3)
Modeling of Collaborative Service Provision
113(5)
Service Provision Capacities
114(1)
Risk/Return Industrial Expectations
115(1)
Pricing
116(1)
Revenue Sharing Schemes
116(2)
Properties of the Models and Implementation Issues
118(1)
Case Study
119(3)
Dynamics of Attitudes
122(14)
Simplified Model: Direct and Indirect Interdependencies
123(2)
Model Formulation
125(5)
Bayesian Networks and Markov Fields
130(1)
Sensitivity Analysis
131(2)
General Interdependencies
133(3)
Conclusion
136(1)
References
136(5)
Part III Analysis and Optimization of Technical Systems and Structures Under Uncertainty
Optimal Ellipsoidal Estimates of Uncertain Systems: An Overview and New Results
141(22)
F.L. Chernousko
Introduction
141(1)
Reachable Sets
142(3)
Ellipsoidal Bounds
145(1)
Optimality
146(2)
Equations of Ellipsoids
148(2)
Transformation of the Equations
150(2)
Properties of Optimal Ellipsoids
152(1)
Generalizations
153(1)
Applications
154(5)
Two-Sided Estimates in Optimal Control
154(1)
Two-Sided Bounds on Time for the Time-Optimal Problem
155(1)
Suboptimal Control
155(1)
Differential Games
156(1)
Control of Uncertain Systems
157(1)
Other Applications
157(1)
State Estimation in the Presence of Observation Errors
158(1)
Ellipsoidal vs. Interval Analysis
159(1)
Conclusions
160(1)
References
160(3)
Expected Total Cost Minimum Design of Plane Frames by Means of Stochastic Linear Programming Methods
163(32)
Kurt Marti
Introduction
164(4)
Plastic Analysis of Structures
164(1)
Limit (Collapse) Load Analysis of Structures as a Linear Programming Problem
165(2)
Plastic and Elastic Design of Structures
167(1)
Plane Frames
168(15)
Yield Condition in Case of M - N - Interaction
173(7)
Approximation of the Yield Condition by Using Reference Capacities
180(3)
Stochastic Optimization
183(8)
Violation of the Yield Condition
184(1)
Cost Function
185(1)
Choice of the Cost Factors
186(1)
Total Costs
187(2)
Discretization Methods
189(1)
Complete Recourse
190(1)
References
191(4)
Part IV Analysis and Optimization of Economic and Engineering Systems Under Uncertainty
Uncertainty in the Future Nitrogen Load to the Baltic Sea Due to Uncertain Meteorological Conditions
195(14)
Jerzy Bartnicki
Introduction
195(3)
Nitrogen Emissions
198(3)
National Emission Ceilings According to EU NEC Directive
198(1)
National Emission Ceilings According to Gothenburg Protocol
199(1)
Nitrogen Emission Projections Used in the Model Runs
200(1)
Computed Nitrogen Depositions for 2010
201(2)
Unified EMEP Model
202(1)
Calculated Depositions to Sub-basins and Catchments of the Baltic Sea
203(1)
Uncertainty Due to Meteorological Variability
203(4)
Conclusions
207(1)
References
207(2)
Planning Sustainable Agricultural Development Under Risks
209(20)
G. Fischer
T. Ermolieva
L. Sun
Introduction
209(2)
Cooperation and Co-existence for Risk Sharing
211(3)
Agricultural Planning Under Risks
214(4)
A Simulation Model
214(2)
A Simplified Production Model
216(1)
A Rebalancing Production-Allocation Algorithm
217(1)
Stochastic Production Allocation Model
218(3)
Numerical Experiments
221(4)
Conclusions
225(1)
References
226(3)
Dealing with Uncertainty in GHG Inventories: How to Go About It?
229(18)
Matthias Jonas
Thomas White
Gregg Marland
Daniel Lieberman
Zbigniew Nahorski
Sten Nilsson
Introduction
230(2)
Does Uncertainty Matter?
232(1)
State of the Art of Analyzing Uncertain Emission Changes
233(5)
How to Deal with Uncertainty?
238(3)
Conclusions
241(1)
References
242(5)
Uncertainty Analysis of Weather Controlled Systems
247(12)
K.J. Keesman
T. Doeswijk
Introduction
247(2)
Preliminaries
249(3)
Bulk Storage Model
249(1)
Weather Forecasts
249(1)
Cost Function
250(1)
Receding Horizon Optimal Control
250(2)
Weather Forecast Uncertainty and Error Analysis
252(4)
Open Loop Evaluation
252(2)
Closed Loop Evaluation
254(2)
Discussion
256(1)
Concluding Remarks
257(1)
References
257(2)
Estimation of the Error in Carbon Dioxide Column Abundances
259(17)
Mitsuhiro Tomosado
Koji Kanefuji
Yukio Matsumoto
Hiroe Tsubaki
Tatsuya Yokota
Introduction
259(2)
Trace Gas Measurement by Satellite Remote Sensing
261(5)
Observations of Trace Gases with Various Sensors
261(1)
GOSAT Mission
262(2)
Previous Error Analysis
264(2)
Error Evaluation and Results
266(10)
Retrieval Method
266(2)
Error Evaluation
268(2)
Error Evaluation Results
270(6)
Conclusions
276(1)
References
276