Incorporating basic hydrological concepts into genetic programming for rainfall-runoff forecasting

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F14%3A59700" target="_blank" >RIV/60460709:41330/14:59700 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/60460709:41330/13:66712

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Incorporating basic hydrological concepts into genetic programming for rainfall-runoff forecasting

Popis výsledku v původním jazyce

This paper focuses on improving rainfall-runoff forecasts by a combination of genetic programming (GP) and basic hydrological modelling concepts. GP is a general optimisation technique for making an automated search of a computer program that solves someparticular problem. The SORD! program was developed for the purposes of this study (in the R programming language). It is an implementation of canonical GP. Special functions are used for a combined approach of hydrological concepts and GP. The specialfunctions are a reservoir model, a simple moving average model, and a cumulative sum and delay operator. The efficiency of the approach presented here is tested on runoff predictions for five catchments of various sizes. The input data consists of dailyrainfall and runoff series. The forecast step is one day. The performance of the proposed approach is compared with the results of the artificial neural network model (ANN) and with the GP model without special functions. GP combined with

Název v anglickém jazyce

Incorporating basic hydrological concepts into genetic programming for rainfall-runoff forecasting

Popis výsledku anglicky

This paper focuses on improving rainfall-runoff forecasts by a combination of genetic programming (GP) and basic hydrological modelling concepts. GP is a general optimisation technique for making an automated search of a computer program that solves someparticular problem. The SORD! program was developed for the purposes of this study (in the R programming language). It is an implementation of canonical GP. Special functions are used for a combined approach of hydrological concepts and GP. The specialfunctions are a reservoir model, a simple moving average model, and a cumulative sum and delay operator. The efficiency of the approach presented here is tested on runoff predictions for five catchments of various sizes. The input data consists of dailyrainfall and runoff series. The forecast step is one day. The performance of the proposed approach is compared with the results of the artificial neural network model (ANN) and with the GP model without special functions. GP combined with

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

DA - Hydrologie a limnologie

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2014

Kód důvěrnosti údajů

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

Název periodika

COMPUTING

ISSN

0010-485X

e-ISSN

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Svazek periodika

95

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

18

Strana od-do

363-380

Kód UT WoS článku

000338630100021

EID výsledku v databázi Scopus

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