Browsing by Subject "regression"

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Analiza ruchu na stronie z wykorzystaniem metod eksploracji danych wraz z prognozowaniem zmian pozycji w wyszukiwarce Google dla wybranej strony www
(Data obrony: 2016-10-24) Misiak, Paweł
Wydział Geologii, Geofizyki i Ochrony Środowiska
Praca magisterska opiera się na statystycznej analizie wizyt na stronie internetowej wraz z przewidywaniem przyszłych pozycji w wyszukiwarce Google. Jej celem jest wykazanie konieczności rezygnacji z usług firmy pozycjonującej a także rozpoznanie współczesnych metod analizy przedmiotowych zagadnień. Do realizacji projektu magisterskiego wykorzystano dwie popularne metody - metoda regresji wielorakiej a także sieci neuronowych. Wyniki analiz pokazały jak zmienia się ilość wizyt na stronie w zależności od okresu roku. W analizach wykorzystano także informacje, czy w danym dniu wystąpiły święta a także czy strona społecznościowa była aktualizowana. W wyniku tych analiz wyciągnięto wnioski, że współczesna strona internetowa nie wymaga tak silnych akcji pozycjonerskich, aby jej pozycja w wyszukiwarce się podniosła. Projekt pozwolił zdobyć szerszą wiedzę na temat pozycjonowania stron a także budowy modeli statystycznych, co będzie mogło zostać wykorzystywane w przyszłości do okresowych analiz wyników pozycjonowania strony.
Access status: Open Access ,
Assessment of the stability of mercury concentrations in municipal waste using data science tools
(Wydawnictwa AGH, 2023) Jędrusiak, Radosław; Chuchro, Monika; Bielowicz, Barbara; Gielar, Agnieszka
Mercury and its compounds are among the most dangerous and toxic substances in the environment. As part of the study, several exploratory analyses and statistical tests were conducted to demonstrate how low and stable mercury content is in municipal waste. A statistical analysis of the mercury content in waste (waste codes 19 12 12 and 20 03 01) was carried out using advanced IT tools. Based on 32 results for each waste, the maximum mercury concentration was 0.062 mg/kg dry weight (EWC code 19 12 12) and 0.052 mg/kg dry weight (EWC code 20 03 01). The analysis, data inference, and modeling were performed according to the CRISP-dm methodology. The results obtained were compared with the maximum allowable mercury concentrations for agricultural soils (2 mg/kg dry weight) and the provisions of the Minamata Convention (1 mg/kg). The average, median, and maximum observed mercury concentrations in waste are significantly lower than the assumed levels of 2 mg/kg (permissible concentrations for II-1 soils) and 1 mg/kg (Minamata Convention). The stability of mercury content in waste was examined. Descriptive statistics, statistical tests, and regression modeling were used. The tests and analyses performed showed an insignificant variation in the mercury content of the wastes with codes 19 12 12 and 20 03 01. No trend or seasonality was observed. The analyses and tests performed confirmed that the data are stable, and the values are low.
Access status: Open Access ,
Change in the structure of electricity generation in the USA, China, Japan and the EU, and a forecast of electricity consumption
(2017) Cieślik, Tomasz
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 14 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 $CO_2$ emission, contrary to the situation in the United States, where, despite an increase in energy consumption and an increase in generation capacity, $CO_2$ emission has been falling since 2005. The largest decrease in $CO_2$ 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).
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Design and implementation of a neural network of object pose regression
(Data obrony: 2019-10-25) Słabuszewska, Anna
Wydział Informatyki, Elektroniki i Telekomunikacji
Access status: Open Access ,
Hybrid model of the conventional power unit
(Wydawnictwa AGH, 2008) Rusinowski, Henryk; Szapajko, Grzegorz; Stanek, Wojciech
The paper presents the hybrid model of the conventional power unit. The model contains following fragmentary models: model of the boiler, turbine and regenerative heat exchangers. Fragmentary models have been elaborated with the application of the analytical modelling methods, regression and neural networks. Hybrid model of the boiler contains balance model compatible with the German norm DIN and regressive models describing content of the unburnt combustibles in the slag and in the dust and the neural model describing the flue gases temperature at the outlet of the boiler. Model of the turbine contains balance model and theoretical-empirical model of the steam expansion line in the turbine. Models of the heat exchangers contain the balance and empirical models describing the heat transfer. The paper presents the exemplary calculation results and their comparison with the measurements.
Access status: Open Access ,
Monitoring of land surface temperature from Landsat imagery - a case study of Al-Anbar Governorate in Iraq
(Wydawnictwa AGH, 2023) Morsy, Salem; Ahmed, Shaker
Land surface temperature (LST) estimation is a crucial topic for many applications related to climate, land cover, and hydrology. In this research, LST estimation and monitoring of the main part of Al-Anbar Governorate in Iraq is presented using Landsat imagery from five years (2005, 2010, 2015, 2016 and 2020). Images of the years 2005 and 2010 were captured by Landsat 5 (TM) and the others were captured by Landsat 8 (OLI/TIRS). The Single Channel Algorithm was applied to retrieve the LST from Landsat 5 and Landsat 8 images. Moreover, the land use/land cover (LULC) maps were developed for the five years using the maximum likelihood classifier. The difference in the LST and normalized difference vegetation index (NDVI) values over this period was observed due to the changes in LULC. Finally, a regression analysis was conducted to model the relationship between the LST and NDVI. The results showed that the highest LST of the study area was recorded in 2016 (min = 21.1°C, max = 53.2°C and mean = 40.8°C). This was attributed to the fact that many people were displaced and had left their agricultural fields. Therefore, thousands of hectares of land which had previously been green land became desertified. This conclusion was supported by comparing the agricultural land areas registered throughout the presented years. The polynomial regression analysis of LST and NDVI revealed a better coefficient of determination (R2) than the linear regression analysis with an average R2 of 0.423.
Access status: Restricted ,
Porównanie różnych narzędzi analizy przepływu danych w strukturach grafowych – sieci neuronowe, metody statystyczne i wnioskowanie rozmyte
(Data obrony: 2018-02-05) Kukla, Jakub
Wydział Geologii, Geofizyki i Ochrony Środowiska
Celem niniejszego projektu jest porównanie różnych narzędzi analizy przepływu danych w strukturach grafowych. Wykorzystuje on dane zgromadzone przez detektory mierzące natężenie ruchu w wielu miejscach Krakowa. Zadanie polegało na sprawdzeniu, czy występują zależności pomiędzy ruchem samochodowym na różnych ulicach Krakowa. Za pomocą sieci neuronowej, metod statystycznych i wnioskowania rozmytego sprawdzono możliwość krótkotrwałej predykcji danych w celu kontrolowania systemu oświetlenia miejskiego.