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001 u371261
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007 cr nn 008mamaa
008 100301s2010 xxu| s |||| 0|eng d
020 _a9781441911292
_9978-1-4419-1129-2
040 _cMX-MeUAM
050 4 _aGE300-350
082 0 4 _a363.7063
_223
100 1 _aFilar, Jerzy A.
_eeditor.
245 1 0 _aUncertainty and Environmental Decision Making
_h[recurso electrónico] :
_bA Handbook of Research and Best Practice /
_cedited by Jerzy A. Filar, Alain Haurie.
264 1 _aBoston, MA :
_bSpringer US,
_c2010.
300 _bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v138
505 0 _aOR/MS and Environmental Decision Making under Uncertainty -- Modeling Uncertainty in a Large scale integrated Energy-Climate Model -- Robust Optimization for Environmental and Energy Planning -- Coping with Climate Risks in Indonesian Rice Agriculture: A Policy Perspective -- A Primer on Weather Derivatives -- Optimal Control Models and Elicitation of Attitudes towards Climate Damages -- A Stochastic Control/Game Approach to the Optimal Timing of Climate Policies -- Precautionary Effect and Variations of the Value of Information -- Comparative Forecasting and a Test for Persistence in the El Niño Southern Oscillation -- Generation of Synthetic Sequences of Electricity Demand with Applications -- Models for Improving Management of Biosolids Odors.
520 _aUncertainty and Environmental Decision Making: A Handbook of Research and Best Practice presents the state of the art in applying operations research and management science (OR/MS) techniques to a broad range of environmental decision making (EDM) challenges. Drawing on leading researchers in the field, it provides a guided tour of selected methods and tools to help deal with issues as climate change, depleting biodiversity and biocapacity, and more general atmospheric, water and soil pollution problems. Individual peer-reviewed chapters look at applying stochastic reasoning on difficult issues arising in EDM under uncertainty; applying stochastic or robust programming methods to techno-economic modeling of energy/environment interactions; important consequences of uncertainty inherent in weather patterns, the El Nino phenomenon and anticipated climate change; exploiting tools of decision analysis, utility theory and optimal control theory to account for differences in time scales between human development processes and the natural processes of the biosphere; and methods that combine statistical and decision analyses that can support a variety of environmental management problems. This important new work will be of special interest to a wide range of researchers, students, and practitioners in environmental economics, OR/MS, environmental and earth sciences, climatologists, and risk assessment.
650 0 _aEnvironmental sciences.
650 0 _aEnvironmental management.
650 0 _aRegional economics.
650 0 _aEnvironmental economics.
650 1 4 _aEnvironment.
650 2 4 _aEnvironmental Monitoring/Analysis.
650 2 4 _aOperations Research/Decision Theory.
650 2 4 _aMath. Appl. in Environmental Science.
650 2 4 _aEnvironmental Management.
650 2 4 _aRegional/Spatial Science.
650 2 4 _aEnvironmental Economics.
700 1 _aHaurie, Alain.
_eeditor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781441911285
830 0 _aInternational Series in Operations Research & Management Science,
_x0884-8289 ;
_v138
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-1-4419-1129-2
596 _a19
942 _cLIBRO_ELEC
999 _c199141
_d199141