Genetic Programming Based Approach Towards Understanding the Dynamics of Urban Rainfall-runoff Process

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41330%2F16%3A71164" target="_blank" >RIV/60460709:41330/16:71164 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.proeng.2016.07.601" target="_blank" >http://dx.doi.org/10.1016/j.proeng.2016.07.601</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.proeng.2016.07.601" target="_blank" >10.1016/j.proeng.2016.07.601</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Genetic Programming Based Approach Towards Understanding the Dynamics of Urban Rainfall-runoff Process

Popis výsledku v původním jazyce

Genetic Programming (GP) is an evolutionary-algorithm based methodology that is the best suited to model non-linear dynamic systems. The potential of GP has not been exploited to the fullest extent in the field of hydrology to understand the complex dynamics involved. The state of the art applications of GP in hydrological modelling involve the use of GP as a short-term prediction and forecast tool rather than as a framework for the development of a better model that can handle current challenges. In today is scenario, with increasing monitoring programmes and computational power, the techniques like GP can be employed for the development and evaluation of hydrological models, balancing, prior information, model complexity, and parameter and output uncertainty. In this study, GP based data driven model in a single and multi-objective framework is trained to capture the dynamics of the urban rainfall-runoff process using a series of tanks, where each tank is a storage unit in a watershed that correspo

Název v anglickém jazyce

Genetic Programming Based Approach Towards Understanding the Dynamics of Urban Rainfall-runoff Process

Popis výsledku anglicky

Genetic Programming (GP) is an evolutionary-algorithm based methodology that is the best suited to model non-linear dynamic systems. The potential of GP has not been exploited to the fullest extent in the field of hydrology to understand the complex dynamics involved. The state of the art applications of GP in hydrological modelling involve the use of GP as a short-term prediction and forecast tool rather than as a framework for the development of a better model that can handle current challenges. In today is scenario, with increasing monitoring programmes and computational power, the techniques like GP can be employed for the development and evaluation of hydrological models, balancing, prior information, model complexity, and parameter and output uncertainty. In this study, GP based data driven model in a single and multi-objective framework is trained to capture the dynamics of the urban rainfall-runoff process using a series of tanks, where each tank is a storage unit in a watershed that correspo

Druh

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

CEP obor

DA - Hydrologie a limnologie

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2016

Kód důvěrnosti údajů

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

Název periodika

Procedia Engineering

ISSN

1877-7058

e-ISSN

—

Svazek periodika

2016

Číslo periodika v rámci svazku

154

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

10

Strana od-do

1093-1102

Kód UT WoS článku

000385793200147

EID výsledku v databázi Scopus

—