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Fuzzy Systems Modeling In Environmental And Health Risk Assessment at Meripustak

Fuzzy Systems Modeling In Environmental And Health Risk Assessment by Faybishenko, John Wiley

Books from same Author: Faybishenko

Books from same Publisher: John Wiley

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  • General Information  
    Author(s)Faybishenko
    PublisherJohn Wiley
    Edition1st Edition
    ISBN9781119569473
    Pages336
    BindingHardcover
    LanguageEnglish
    Publish YearMarch 2023

    Description

    John Wiley Fuzzy Systems Modeling In Environmental And Health Risk Assessment by Faybishenko

    Fuzzy Systems Modeling in Environmental and Health Risk AssessmentDemonstrates the successful application of fuzzy systems modeling to real-world environmental and health problemsIn 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 environmental sciencePractical advice on environmental quality assessments and human health risk analysesIn-depth case studies involving air and water pollution, solid waste, indoor swimming pool and landfill risk assessments, wastewater treatment, and morePerfect for environmental engineers and scientists, Fuzzy Systems Modeling in Environmental and Health Risk Assessment will also benefit policy makers, computer scientists, mathematicians, and researchers and practitioners interested in applying soft computing theories to environmental problems.



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