Fuzzy Systems Modeling in Environmental and Health Risk Assessment
Author | : Boris Faybishenko |
Publisher | : John Wiley & Sons |
Total Pages | : 340 |
Release | : 2023-03-13 |
ISBN-13 | : 9781119569480 |
ISBN-10 | : 1119569486 |
Rating | : 4/5 (86 Downloads) |
Download or read book Fuzzy Systems Modeling in Environmental and Health Risk Assessment written by Boris Faybishenko and published by John Wiley & Sons. This book was released on 2023-03-13 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fuzzy Systems Modeling in Environmental and Health Risk Assessment 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 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, 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.