Stochastic model and optimum sampling interval of variables for environmental measurement systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F17%3A39911384" target="_blank" >RIV/00216275:25410/17:39911384 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/00216275:25530/17:39911384

Výsledek na webu

<a href="http://dx.doi.org/10.1109/EPE.2017.7967328" target="_blank" >http://dx.doi.org/10.1109/EPE.2017.7967328</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/EPE.2017.7967328" target="_blank" >10.1109/EPE.2017.7967328</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Stochastic model and optimum sampling interval of variables for environmental measurement systems

Popis výsledku v původním jazyce

It is common in engineering to model time-dependent variables as diffusion process represented by stochastic differential equations. This is usually helpful when empirical datasets describing time evolution of variables are available. This helps in accurate estimation of parameters of the stochastic differential equation which describes the dynamic system. Additionally, it helps in characterization and determination of optimal performance of the system. The above have been conducted in this study using real environmental field data. Linear stochastic model was fitted to longitudinal datasets and optimum sampling interval investigated. A new method has been proposed for determination of optimum sampling interval. Results obtained differ from those of hypothetical optimum which do not take energy consumption into consideration.

Název v anglickém jazyce

Stochastic model and optimum sampling interval of variables for environmental measurement systems

Popis výsledku anglicky

It is common in engineering to model time-dependent variables as diffusion process represented by stochastic differential equations. This is usually helpful when empirical datasets describing time evolution of variables are available. This helps in accurate estimation of parameters of the stochastic differential equation which describes the dynamic system. Additionally, it helps in characterization and determination of optimal performance of the system. The above have been conducted in this study using real environmental field data. Linear stochastic model was fitted to longitudinal datasets and optimum sampling interval investigated. A new method has been proposed for determination of optimum sampling interval. Results obtained differ from those of hypothetical optimum which do not take energy consumption into consideration.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2017

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 18th International Scientific Conference on Electric Power Engineering, EPE 2017

ISBN

978-1-5090-6405-2

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

5

Strana od-do

"xx"

Název nakladatele

IEEE (Institute of Electrical and Electronics Engineers)

Místo vydání

New York

Místo konání akce

Kouty nad Desnou

Datum konání akce

17. 5. 2017

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000422921000094