Statistická analýza výsledků geologického průzkumu
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Date
Authors
Mansoor, Mohsin
ORCID
Advisor
Referee
Mark
E
Journal Title
Journal ISSN
Volume Title
Publisher
Vysoké učení technické v Brně. Fakulta strojního inženýrství
Abstract
The statistical analysis of data from geological surveys is the main focus of this thesis, which looks at how CO2 concentrations change over time. The study examines the complex relationships that exist between different environmental factors and CO2 levels using multiple linear regression models. The models incorporate cosinusoidal and sinusoidal components to capture daily averages, thereby accounting for data variations throughout the year. In-depth residual analysis and autocorrelation studies are used in the research to assess the model’s performance and guarantee that the models are reliable and accurate in predicting CO2 levels. This study offers a solid basis for future research and improves the knowledge of soil behavior.
The statistical analysis of data from geological surveys is the main focus of this thesis, which looks at how CO2 concentrations change over time. The study examines the complex relationships that exist between different environmental factors and CO2 levels using multiple linear regression models. The models incorporate cosinusoidal and sinusoidal components to capture daily averages, thereby accounting for data variations throughout the year. In-depth residual analysis and autocorrelation studies are used in the research to assess the model’s performance and guarantee that the models are reliable and accurate in predicting CO2 levels. This study offers a solid basis for future research and improves the knowledge of soil behavior.
The statistical analysis of data from geological surveys is the main focus of this thesis, which looks at how CO2 concentrations change over time. The study examines the complex relationships that exist between different environmental factors and CO2 levels using multiple linear regression models. The models incorporate cosinusoidal and sinusoidal components to capture daily averages, thereby accounting for data variations throughout the year. In-depth residual analysis and autocorrelation studies are used in the research to assess the model’s performance and guarantee that the models are reliable and accurate in predicting CO2 levels. This study offers a solid basis for future research and improves the knowledge of soil behavior.
Description
Citation
MANSOOR, M. Statistická analýza výsledků geologického průzkumu [online]. Brno: Vysoké učení technické v Brně. Fakulta strojního inženýrství. 2024.
Document type
Document version
Date of access to the full text
Language of document
en
Study field
bez specializace
Comittee
doc. Ing. Luděk Nechvátal, Ph.D. (předseda)
prof. RNDr. Miloslav Druckmüller, CSc. (místopředseda)
prof. Mgr. Pavel Řehák, Ph.D. (člen)
doc. RNDr. Jiří Tomáš, Dr. (člen)
doc. Mgr. et Mgr. Aleš Návrat, Ph.D. (člen)
Mariapia Palombaro (člen)
Gennaro Ciampa (člen)
Matteo Colangeli (člen)
Carmela Scalone (člen)
Date of acceptance
2024-10-04
Defence
The student presented his master's thesis on the topic: Statistical analysis of geological survey results. After the presentation, the reviews of the supervisor and opponent were read. Student was able to partially react to the oppononet's comments.
Result of defence
práce byla úspěšně obhájena
Document licence
Standardní licenční smlouva - přístup k plnému textu bez omezení