Fuzzy Systems Modeling in Environmental and Health Risk Assessment

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  • Fuzzy Systems Modeling in Environmental and Health Risk Assessment Book Detail

  • Author : Boris Faybishenko
  • Release Date : 2023-04-04
  • Publisher : John Wiley & Sons
  • Genre : Science
  • Pages : 340
  • ISBN 13 : 1119569478
  • File Size : 75,75 MB

Fuzzy Systems Modeling in Environmental and Health Risk Assessment by Boris Faybishenko PDF Summary

Book Description: Demonstrates the successful application of fuzzy systems modeling to real-world environmental and health problems In Fuzzy Systems Modeling in Environmental and Health Risk Assessment, a team of distinguished researchers delivers an up-to-date collection of the most successful and innovative attempts to apply fuzzy logic to problems involving environmental risk assessment, healthcare decision-making, the management of water distribution networks, and the optimization of water treatment and waste management systems. By explaining both the theoretical and practical aspects of using fuzzy systems modeling methods to solve complex problems, analyze risks and optimize system performance, this handy guide maintains a strongly application-oriented perspective throughout, offering readers a practical treatment of a cutting-edge subject. Readers will also find: Comprehensive explorations of the practical applications of fuzzy systems modeling in hydrogeology and environmental science Practical advice on environmental quality assessments and human health risk analyses In-depth case studies involving air and water pollution, solid waste, indoor swimming pool and landfill risk assessments, wastewater treatment, and more Perfect for environmental engineers and scientists, hydrogeologists and geologists, Fuzzy Systems Modeling in Environmental and Health Risk Assessment will also benefit policy makers, mathematicians, theoretical hydrologists, and researchers and practitioners interested in applying soft computing theories to environmental problems.

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Fuzzy Systems

Fuzzy Systems

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The analysis and control of complex systems have been the main motivation for the emergence of fuzzy set theory since its inception. It is also a major research