Incorporating climate change into risk assessment using grey mathematical programming.

Part of a special issue on climate change and variability, uncertainty, and decision making. Climate change presents problems for risk assessment procedures because of the difficulty associated with assigning a measure of probability to any future scenario. Grey systems theory, however, provides a...

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Publicado en:Journal of Environmental Management Vol. 49; pp. 107 - 124
Autores principales: Bass, Brad, Huang, Guohe, Russo, Joe
Formato: Artículo
Publicado: Academic Press Inc. January 1997
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: January 1997
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      pub: Academic Press Inc.
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        atl: Incorporating climate change into risk assessment using grey mathematical programming.
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          Bass, Brad
          Huang, Guohe
          Russo, Joe
      su:
        Risk assessment
        Mathematical programming
        Environmental impact analysis
        Probability theory
        Climate change
        Climatology
        Meteorology statistical methods
        Uncertainty
        Economics
      sug:
        subj:
          Risk assessment
          Mathematical programming
          Environmental impact analysis
          Probability theory
          Climate change
          Climatology
          Meteorology statistical methods
          Uncertainty
          Economics
      ab: Part of a special issue on climate change and variability, uncertainty, and decision making. Climate change presents problems for risk assessment procedures because of the difficulty associated with assigning a measure of probability to any future scenario. Grey systems theory, however, provides an alternative method of quantifying uncertainty that is based on interval numbers. Grey systems theory within a mathematical programming model provides a means for working with uncertainties that are not amenable to stochastic or fuzzy quantification. The writers use an example of forestry and agricultural expansion in the Mackenzie River Basin to demonstrate grey mathematical programming in a hop, skip, and jump formulation, and their analysis demonstrates that a grey mathematical programming algorithm is useful for assessing the sensitivity of a decision to climatically sensitive parameters.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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