文档介绍：外文原文
Fuzzy approaches to environmental decisions: applicationto air quality
Bernard . Fisher
a b s t r a c t
This paper considers flexible approaches to decisions designed to improve environmental quality having regard to uncertainty. The performance of simple plex models, for forecasting air quality are reviewed, and both types are shown to involve considerable uncertainty regarded as typical of environmental systems. This means that decisions usually depend bining two or more quite uncertain environmental criteria, and it is shown that this can be approached systematically if a fuzzy logic framework is adopted. Fuzzy set aggregation includes, as special cases, other decision-making frameworks, such as multi-criteria analysis and conventional probability based methods. Examples are presented of how it can be applied to situations involving models and used to incorporate broader factors involving risk, and socio-economic considerations.
1. The problem
Ideally environmental models should contain the bestknown science, be tested against measurements, and then used for prediction and decision-making if they are supported by the necessary input data and perform well against measurements. This has led in recent years to the development of plex, fundamental models, in which every part of the environmental system is described in as much detail as possible, the so-called ‘reductionist’ approach. If the development in modelling produced better predictions this would be the way to proceed. From examples in the field of air pollution, it is argued in this paper that limitations in process description, and the lack of detailed data on concentrations, deposition or emissions etc., mean that this approach has not produced usefully better predictions. Even the most advanced models are still associated with large uncertainties (
Hunt, 2000; Funtowicz and Ravetz, 2005; Saloranta, 2001).
The alternative approach to forecasting is to consider the decision that is likely to