Some Possibilities For Construction Of Linguistic Variables For Sustainable Development Decision Making

- Organization:
- Society for Mining, Metallurgy & Exploration
- Pages:
- 6
- File Size:
- 68 KB
- Publication Date:
- Jan 1, 2007
Abstract
Fuzzy logic is a useful tool for Sustainable Development (SD) decision making because it can express uncertainty, both in the informational and in the decision-making environment. The general linguistic definition, acceptability for environment (air, water, nature, risk, etc.), as well other aspects of sustainable development (health, management issues, etc) is proved to be useful in approximate reasoning and decision-making. According to this definition, the various fuzzy functions of environmental acceptability can be constructed. This construction is based on the concept of special kinds of fuzzy functions generally defined as Linguistic Variables (LV), which are suitable for mapping to fuzzy sets. Various SD indicators could be used as domains of such functions, expressed either in their physical values (e.g. production, emissions, risk of accidents) or in Measure of Preferences (MP). The most important MP are mentioned below: Stated Preferences Techniques (SPT) of economic evaluation of environment, economic instruments of environmental protection mostly based on Revealed Preference Techniques (RPT), preferences scales (ordinal, cardinal) according to various methods of their construction, etc. Also, the possibility theory (analogous to probability) could be exploited in such construction. It could be used together with environmental engineering modelling formulas for the purpose of determining fuzzy functions. The appropriate forms of linguistic variables, considering limit cases for this purpose, are also discussed.
Citation
APA:
(2007) Some Possibilities For Construction Of Linguistic Variables For Sustainable Development Decision MakingMLA: Some Possibilities For Construction Of Linguistic Variables For Sustainable Development Decision Making. Society for Mining, Metallurgy & Exploration, 2007.