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Probabilistic and fuzzy approaches for uncertainty consideration in water distribution networks – a review
Author(s) -
Prerna Pandey,
Shilpa Dongre,
Rajesh Gupta
Publication year - 2019
Publication title -
water science and technology water supply
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 39
eISSN - 1607-0798
pISSN - 1606-9749
DOI - 10.2166/ws.2019.141
Subject(s) - probabilistic logic , fuzzy logic , reliability (semiconductor) , computer science , uncertainty quantification , uncertain data , possibility theory , uncertainty analysis , probability distribution , mathematical optimization , key (lock) , data mining , reliability engineering , fuzzy set , machine learning , mathematics , artificial intelligence , engineering , statistics , simulation , power (physics) , physics , computer security , quantum mechanics
The performance of water distribution system of providing a required flow rate at all the nodes with required pressure heads throughout its design life is affected by uncertainties associated with different parameters such as future water demands, pipe roughness coefficient values, required pressure heads at nodes, etc. The objective of this paper is to present a comprehensive review on the nature of uncertainties (random or fuzzy), various models and methods used for their quantification, and different ways of handling them in the design of water distribution networks. While the probabilistic based approaches are used for handling the uncertainty of random type, the possibilistic based approach considers the uncertainty of fuzzy nature. Some key issues and serious limitations of the existing approaches for modeling uncertain parameters related to water distribution networks are identified. The uncertainty in water demands is due to both, their random nature and lack of information about their values. Therefore, a combination of both types of approaches, called fuzzy random approach is found to be more effective. Fuzzy Random approach can provide optimal design solutions that are not only cost-effective but also has higher reliability to cope with severe future uncertainties. doi: 10.2166/ws.2019.141 s://iwaponline.com/ws/article-pdf/doi/10.2166/ws.2019.141/607052/ws2019141.pdf Prerna Pandey (corresponding author) Shilpa Dongre Rajesh Gupta Civil Engineering Department, Visvesvaraya National Institute of Technology (VNIT), Nagpur 440010, Maharashtra, India E-mail: prerna.pandey1203@gmail.com

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