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Wyświetlanie 1-3 z 3
Tytuł:
Change in the structure of electricity generation in the USA, China, Japan and the EU, and a forecast of electricity consumption
Autorzy:
Cieślik, T.
Powiązania:
https://bibliotekanauki.pl/articles/298856.pdf
Data publikacji:
2017
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
electricity
emission
regression
forecasting
energy sector
Opis:
This article analyses changes in the structure of electricity production in countries such as the USA, China, Japan, the EU and Poland. In China, a sharp increase in generation capacity and electricity production may be noticed if the data from 2015 and 1990 is compared. The increase in China’s electricity production is associated with a continuous growth in CO2 emission, contrary to the situation in the United States, where, despite an increase in energy consumption and an increase in generation capacity, CO2 emission has been falling since 2005. The largest decrease in CO2 emission without inhibiting the growth of electricity production and electricity consumption can be seen in the EU. Models of consumption have been determined based on the collected data such as: temperature, dummy variables and electricity consumption per hour within three months. The aim was to establish the best regression model and compare it to the neural network models using mean absolute percentage error (MAPE).
Źródło:
AGH Drilling, Oil, Gas; 2017, 34, 1; 291-302
2299-4157
2300-7052
Pojawia się w:
AGH Drilling, Oil, Gas
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modeling of gas consumption in the city
Autorzy:
Cieślik, T.
Metelska, K.
Powiązania:
https://bibliotekanauki.pl/articles/299233.pdf
Data publikacji:
2017
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
gas
gas consumption
models
Opis:
Based on the data collected over a two year time period, which included temperature, wind speed and gas consumption during the day, the effects of weather factors on gas consumption in the city have been established with the use of multiple regression. The impact of a particular month, day (dummy variable) or holiday of a year on the gas consumption has also been determined. The models of linear regression and artificial neural networks have been constructed for determining the gas consumption. An attempt has been made to find the best regression models and compare them to the neural network models with the use of mean absolute percentage error (MAPE).
Źródło:
AGH Drilling, Oil, Gas; 2017, 34, 2; 439-453
2299-4157
2300-7052
Pojawia się w:
AGH Drilling, Oil, Gas
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A review of currently available LNG facilities and means of transport used for supplying terminals in natural gas with a projection of LNG prices in the USA
Autorzy:
Metelska, K.
Cieślik, T.
Powiązania:
https://bibliotekanauki.pl/articles/298697.pdf
Data publikacji:
2016
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
LNG
LNG transport
LNG storage
Opis:
LNG terminals allow for constant availability of fuel gas in insular countries (Japan) and in countries which do not have the option of transporting gas via inland pipelines due to their geopolitical location (South Korea). In many cases, possessing an LNG (liquefied natural gas) terminal increases energy independence, which translates first and foremost into avoiding energy blackmail (Lithuania). This paper presents currently existing LNG terminals together with an overview of the most widely used technologies for gas liquefaction, storage and long-distance transporting by LNG carriers. A comparison of natural gas liquefaction plants and LNG terminals with respect to their location, age and capacity is also given. In the final part of the paper we analyse LNG carriers in relation to age, capacity and shipowner. On the basis of data collected in the last 12 years, such as: price of LNG exported from USA, prices of imported and exported natural gas, consumption of gas, we have established the price of imported LNG using linear regression and power functions. In order to determine the price of LNG we have constructed mathematical models by means of the STATISTICA program. Our aim was to find the most accurate model. Three basic ex post methods have been used to compare regression models: ME (mean error), RMSE (root mean squared error), MAPE (mean absolute percentage error).
Źródło:
AGH Drilling, Oil, Gas; 2016, 33, 1; 49-67
2299-4157
2300-7052
Pojawia się w:
AGH Drilling, Oil, Gas
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

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