These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

151 related articles for article (PubMed ID: 32707306)

  • 1. Vulnerability analysis of water distribution networks to accidental pipe burst.
    Wéber R; Huzsvár T; Hős C
    Water Res; 2020 Oct; 184():116178. PubMed ID: 32707306
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Hydraulically informed graph theoretic measure of link criticality for the resilience analysis of water distribution networks.
    Ulusoy AJ; Stoianov I; Chazerain A
    Appl Netw Sci; 2018; 3(1):31. PubMed ID: 30839751
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Graph Laplace Regularization-based pressure sensor placement strategy for leak localization in the water distribution networks under joint hydraulic and topological feature spaces.
    Cheng M; Li J; Wang C; Ye C; Chang Z
    Water Res; 2024 Jun; 257():121666. PubMed ID: 38703543
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Deep learning identifies accurate burst locations in water distribution networks.
    Zhou X; Tang Z; Xu W; Meng F; Chu X; Xin K; Fu G
    Water Res; 2019 Dec; 166():115058. PubMed ID: 31536886
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Generic patterns in the evolution of urban water networks: Evidence from a large Asian city.
    Krueger E; Klinkhamer C; Urich C; Zhan X; Rao PSC
    Phys Rev E; 2017 Mar; 95(3-1):032312. PubMed ID: 28415303
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A Risk-Based Approach in Rehabilitation of Water Distribution Networks.
    Raspati GS; Bruaset S; Bosco C; Mushom L; Johannessen B; Ugarelli R
    Int J Environ Res Public Health; 2022 Jan; 19(3):. PubMed ID: 35162616
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Modeling complexity in engineered infrastructure system: Water distribution network as an example.
    Zeng F; Li X; Li K
    Chaos; 2017 Feb; 27(2):023105. PubMed ID: 28249393
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Morphogenesis of Urban Water Distribution Networks: A Spatiotemporal Planning Approach for Cost-Efficient and Reliable Supply.
    Zischg J; Rauch W; Sitzenfrei R
    Entropy (Basel); 2018 Sep; 20(9):. PubMed ID: 33265797
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Real time control of water distribution networks: A state-of-the-art review.
    Creaco E; Campisano A; Fontana N; Marini G; Page PR; Walski T
    Water Res; 2019 Sep; 161():517-530. PubMed ID: 31229732
    [TBL] [Abstract][Full Text] [Related]  

  • 10. A growth model for water distribution networks with loops.
    Sugishita K; Abdel-Mottaleb N; Zhang Q; Masuda N
    Proc Math Phys Eng Sci; 2021 Nov; 477(2255):20210528. PubMed ID: 35153598
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Increasing the capacity of water distribution networks using fitness function transformation.
    Huzsvár T; Wéber R; Déllei Á; Hős C
    Water Res; 2021 Aug; 201():117362. PubMed ID: 34174728
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Reconstructing transient pressures in pipe networks from local observations by using physics-informed neural networks.
    Ye J; Zeng W; Do NC; Lambert M
    Water Res; 2024 Jun; 257():121648. PubMed ID: 38663215
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Hyperparameter Optimization of a Convolutional Neural Network Model for Pipe Burst Location in Water Distribution Networks.
    Antunes A; Ferreira B; Marques N; Carriço N
    J Imaging; 2023 Mar; 9(3):. PubMed ID: 36976119
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Comparison of topological, empirical and optimization-based approaches for locating quality detection points in water distribution networks.
    Santonastaso GF; Di Nardo A; Creaco E; Musmarra D; Greco R
    Environ Sci Pollut Res Int; 2021 Jul; 28(26):33844-33853. PubMed ID: 32851529
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Bridging hydraulics and graph signal processing: A new perspective to estimate water distribution network pressures.
    Zhou X; Liu S; Xu W; Xin K; Wu Y; Meng F
    Water Res; 2022 Jun; 217():118416. PubMed ID: 35429881
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A risk-based soft sensor for failure rate monitoring in water distribution network via adaptive neuro-fuzzy interference systems.
    Gheibi M; Moezzi R; Taghavian H; Wacławek S; Emrani N; Mohtasham M; Khaleghiabbasabadi M; Koci J; Yeap CSY; Cyrus J
    Sci Rep; 2023 Jul; 13(1):12200. PubMed ID: 37500665
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Real-time water quality prediction in water distribution networks using graph neural networks with sparse monitoring data.
    Li Z; Liu H; Zhang C; Fu G
    Water Res; 2024 Feb; 250():121018. PubMed ID: 38113592
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Many-objective optimization model for the flexible design of water distribution networks.
    Marques J; Cunha M; Savić D
    J Environ Manage; 2018 Nov; 226():308-319. PubMed ID: 30125810
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Enhancing reclaimed water distribution network resilience with cost-effective meshing.
    Martínez D; Bergillos S; Corominas L; Comas J; Wang F; Kooij R; Calle E
    Sci Total Environ; 2024 Aug; 938():173051. PubMed ID: 38740194
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Hydraulic performance benchmarking for effective management of water distribution networks: An innovative composite index-based approach.
    Zaman D; Gupta AK; Uddameri V; Tiwari MK; Ghosal PS
    J Environ Manage; 2021 Dec; 299():113603. PubMed ID: 34454199
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.