Fuzzy Methods For Assessment And Decision Making
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Quantifying Environmental Impact Assessments Using Fuzzy Logic
Author: Richard B. Shepard
language: en
Publisher: Springer Science & Business Media
Release Date: 2006-10-14
Environmental impact assessments are required for a wide-range of projects throughout the world. These assessments have increasing involved complex, political decision-making and incorporated values and beliefs of both stakeholders and interested parties. However, the results are often ineffective because values and beliefs are not easily quantifiable, and decisions are considered subjective. This analysis recognizes these problems and proposes practical methods based on fuzzy logic that will enable people preparing assessments to define terms and quantify opinions and input so that they are agreed upon by all involved parties. Fuzzy logic also quantifies the complex environmental, economic and social conditions that are present and are predicted by project alternatives. The author places special emphasis on the types of issues that frequently arise in NEPA environmental assessments and environmental impact statements and in similar regulations that are used in jurisdictions regionally and internationally. The new methods are intended to reduce the time and cost of assessments, while producing justifiable results. First, issues related to current environmental impact assessment methods are discussed. Then the book discusses how lessons learned from computational intelligence can address these problems. It describes how a systematic, logical approach to environmental assessment can be applied to a variety of complex situations. Finally, the design and implementation of a more objective and powerful assessment is demonstrated through a worked example. Explanations of computational intelligence techniques and discussions of helpful software are intended to benefit those people actually preparing and using environmental assessments--in language that makes the process transparent and transferable to all types of systems.
Fuzzy Decision Making In Modeling And Control
Author: Joao M Costa Sousa
language: en
Publisher: World Scientific
Release Date: 2002-12-03
Decision making and control are two fields with distinct methods for solving problems, and yet they are closely related. This book bridges the gap between decision making and control in the field of fuzzy decisions and fuzzy control, and discusses various ways in which fuzzy decision making methods can be applied to systems modeling and control.Fuzzy decision making is a powerful paradigm for dealing with human expert knowledge when one is designing fuzzy model-based controllers. The combination of fuzzy decision making and fuzzy control in this book can lead to novel control schemes that improve the existing controllers in various ways. The following applications of fuzzy decision making methods for designing control systems are considered:• Fuzzy decision making for enhancing fuzzy modeling. The values of important parameters in fuzzy modeling algorithms are selected by using fuzzy decision making.• Fuzzy decision making for designing signal-based fuzzy controllers. The controller mappings and the defuzzification steps can be obtained by decision making methods.• Fuzzy design and performance specifications in model-based control. Fuzzy constraints and fuzzy goals are used.• Design of model-based controllers combined with fuzzy decision modules. Human operator experience is incorporated for the performance specification in model-based control.The advantages of bringing together fuzzy control and fuzzy decision making are shown with multiple examples from real and simulated control systems.
Fuzzy Multi-Criteria Decision Making
Author: Cengiz Kahraman
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-08-09
In trying to make a satisfactory decision when imprecise and multicriteria situations are involved, a decision maker has to use a fuzzy multicriteria decision making method. "Fuzzy Multi-Criteria Decision Making" (MCDM) presents fuzzy multiattribute and multiobjective decision-making methodologies by distinguished MCDM researchers. In summarizing the concepts and results of the most popular fuzzy multicriteria methods, using numerical examples, this work examines all the fuzzy multicriteria methods recently developed, such as fuzzy AHP, fuzzy TOPSIS, interactive fuzzy multiobjective stochastic linear programming, fuzzy multiobjective dynamic programming, grey fuzzy multiobjective optimization, fuzzy multiobjective geometric programming, and more. Each of the 22 chapters includes practical applications along with new developments/results. This book may be used as a textbook in graduate operations research, industrial engineering, and economics courses. It will also be an excellent resource, providing new suggestions and directions for further research, for computer programmers, mathematicians, and scientists in a variety of disciplines where multicriteria decision making is needed.