Počet záznamů: 1  

Application of random number generators in genetic algorithms to improve rainfall-runoff modelling

  1. 1.
    SYSNO ASEP0480548
    Druh ASEPJ - Článek v odborném periodiku
    Zařazení RIVJ - Článek v odborném periodiku
    Poddruh JČlánek ve WOS
    NázevApplication of random number generators in genetic algorithms to improve rainfall-runoff modelling
    Tvůrce(i) Chlumecký, M. (CZ)
    Buchtele, Josef (UH-J) RID, ORCID, SAI
    Richta, K. (CZ)
    Zdroj.dok.Journal of Hydrology. - : Elsevier - ISSN 0022-1694
    Roč. 553, October (2017), s. 350-355
    Poč.str.6 s.
    Forma vydáníTištěná - P
    Jazyk dok.eng - angličtina
    Země vyd.NL - Nizozemsko
    Klíč. slovagenetic algorithm ; optimisation ; rainfall-runoff modeling ; random generator
    Vědní obor RIVDA - Hydrologie a limnologie
    Obor OECDHydrology
    Institucionální podporaUH-J - RVO:67985874
    UT WOS000412612700027
    EID SCOPUS85027697238
    DOI10.1016/j.jhydrol.2017.08.025
    AnotaceThe efficient calibration of rainfall-runoff models is a difficult issue, even for experienced hydrologists. Therefore, fast and high-quality model calibration is a valuable improvement. This paper describes a novel methodology and software for the optimisation of a rainfall-runoff modelling using a genetic algorithm (GA) with a newly prepared concept of a random number generator (HRNG), which is the core of the optimisation. The GA estimates model parameters using evolutionary principles, which requires a quality number generator. The new HRNG generates random numbers based on hydrological information and it provides better numbers compared to pure software generators. The GA enhances the model calibration very well and the goal is to optimise the calibration of the model with a minimum of user interaction. This article focuses on improving the internal structure of the GA, which is shielded from the user. The results that we obtained indicate that the HRNG provides a stable trend in the output quality of the model, despite various configurations of the GA. In contrast to previous research, the HRNG speeds up the calibration of the model and offers an improvement of rainfall-runoff modelling.
    PracovištěÚstav pro hydrodynamiku
    KontaktSoňa Hnilicová, hnilicova@ih.cas.cz, Tel.: 233 109 003
    Rok sběru2018
Počet záznamů: 1  

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