Can fuzzy logic bring complex problems into focus? Modeling imprecise factors in environmental policy

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In modeling complex environmental problems, we often fail to make precise statements about inputs and outcome. In this case the fuzzy logic method native to the human mind provides a useful way to get at these problems. Fuzzy logic represents a significant change in both the approach to and outcome of environmental evaluations. Risk assessment is currently based on the implicit premise that probability theory provides the necessary and sufficient tools for dealing with uncertainty and variability. The key advantage of fuzzy methods is the way they reflect the human mind in its remarkable ability to store and process information ... continued below

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17 pages

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McKone, Thomas E. & Deshpande, Ashok W. June 14, 2004.

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Description

In modeling complex environmental problems, we often fail to make precise statements about inputs and outcome. In this case the fuzzy logic method native to the human mind provides a useful way to get at these problems. Fuzzy logic represents a significant change in both the approach to and outcome of environmental evaluations. Risk assessment is currently based on the implicit premise that probability theory provides the necessary and sufficient tools for dealing with uncertainty and variability. The key advantage of fuzzy methods is the way they reflect the human mind in its remarkable ability to store and process information which is consistently imprecise, uncertain, and resistant to classification. Our case study illustrates the ability of fuzzy logic to integrate statistical measurements with imprecise health goals. But we submit that fuzzy logic and probability theory are complementary and not competitive. In the world of soft computing, fuzzy logic has been widely used and has often been the ''smart'' behind smart machines. But it will require more effort and case studies to establish its niche in risk assessment or other types of impact assessment. Although we often hear complaints about ''bright lines,'' could we adapt to a system that relaxes these lines to fuzzy gradations? Would decision makers and the public accept expressions of water or air quality goals in linguistic terms with computed degrees of certainty? Resistance is likely. In many regions, such as the US and European Union, it is likely that both decision makers and members of the public are more comfortable with our current system in which government agencies avoid confronting uncertainties by setting guidelines that are crisp and often fail to communicate uncertainty. But some day perhaps a more comprehensive approach that includes exposure surveys, toxicological data, epidemiological studies coupled with fuzzy modeling will go a long way in resolving some of the conflict, divisiveness, and controversy in the current regulatory paradigm.

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17 pages

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OSTI as DE00834236

Interagency Agreement DW-988-38199-01-0 (United States)

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  • Other Information: PBD: 14 Jun 2004

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  • Report No.: LBNL-55457
  • Grant Number: AC03-76SF00098
  • Grant Number: DW-988-38199-01-0
  • DOI: 10.2172/834236 | External Link
  • Office of Scientific & Technical Information Report Number: 834236
  • Archival Resource Key: ark:/67531/metadc785413

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  • June 14, 2004

Added to The UNT Digital Library

  • Dec. 3, 2015, 9:30 a.m.

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  • April 4, 2016, 12:24 p.m.

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McKone, Thomas E. & Deshpande, Ashok W. Can fuzzy logic bring complex problems into focus? Modeling imprecise factors in environmental policy, report, June 14, 2004; Berkeley, California. (digital.library.unt.edu/ark:/67531/metadc785413/: accessed October 17, 2018), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.