Using particle swarm optimization algorithm for parameter estimation in hydrological modelling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F15%3A67974" target="_blank" >RIV/60460709:41330/15:67974 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.5593/SGEM2015/B21/S7.050" target="_blank" >http://dx.doi.org/10.5593/SGEM2015/B21/S7.050</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.5593/SGEM2015/B21/S7.050" target="_blank" >10.5593/SGEM2015/B21/S7.050</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using particle swarm optimization algorithm for parameter estimation in hydrological modelling

Popis výsledku v původním jazyce

The main goal of this paper is to present a new approach in searching of the best set of parameters of the Bilan rainfall-runoff model. The particle swarm optimization technique was used and we compared the results of the PSO algorithms with linearly decreasing inertia weight and PSO with constriction factor. The model was tested on 30 monitored catchments with a length of observation of 54 years. The input data to the model are precipitation, evaporation, and air temperature, and the model simulates the runoff from the basin. The optimization ability of each method was estimated by the Nash-Sutcliffe coefficient, and other accuracy criteria like mean squared error, or mean absolute error was calculated. The results show that the PSO algorithm modifiedby the parameter of linearly decreasing inertia weight gives better estimation of parameters than the algorithm with constriction factor. The findings of this paper increase the usage of the PSO algorithm in real-life optimization proble

Název v anglickém jazyce

Using particle swarm optimization algorithm for parameter estimation in hydrological modelling

Popis výsledku anglicky

The main goal of this paper is to present a new approach in searching of the best set of parameters of the Bilan rainfall-runoff model. The particle swarm optimization technique was used and we compared the results of the PSO algorithms with linearly decreasing inertia weight and PSO with constriction factor. The model was tested on 30 monitored catchments with a length of observation of 54 years. The input data to the model are precipitation, evaporation, and air temperature, and the model simulates the runoff from the basin. The optimization ability of each method was estimated by the Nash-Sutcliffe coefficient, and other accuracy criteria like mean squared error, or mean absolute error was calculated. The results show that the PSO algorithm modifiedby the parameter of linearly decreasing inertia weight gives better estimation of parameters than the algorithm with constriction factor. The findings of this paper increase the usage of the PSO algorithm in real-life optimization proble

Druh

D - Stať ve sborníku

CEP obor

JC - Počítačový hardware a software

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

GeoConference on informatics, geoinformatics and remote sensing

ISBN

978-619-7105-34-6

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

399-406

Název nakladatele

International Multidisciplinary Scientific GeoConference SGEM

Místo vydání

Sofia, Bulgaria

Místo konání akce

Albena, Bulgaria

Datum konání akce

18. 6. 2015

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000371599500050