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Description of Relation between Flow and Suspended Sediment Load in a Hydromertic Profiles of a Selected Rivers
Bobková, Dominika ; Janál,, Petr (referee) ; Marton, Daniel (advisor)
The issue of the relationship between water discharge and the suspended sediment loads is a globally highly addressed topic. Knowing the suspended sediment loads in the streams avoids problems with over-filling of water cannons and thus prevents insufficient capacity of water reservoirs. This thesis is partly a follow-up to the bachelor thesis, which extends and introduces new procedures. Neural networks, more specifically multilayer perceptron neural networks, are used to analyse the relationship between water discharge and suspended sediment loads. The results of the networks are then processed in Excel into graphs and evaluated using the coefficient of determination, Nash-Sutcliffe coefficient and RMSE coefficient. The practical application is solved on two profiles - the profile Podhradí nad Dyjí and the profile Židlochovice. Each profile is examined in a different period.
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Testing early strength concrete by electronic tester
Holbová, Monika ; Kocáb, Dalibor (referee) ; Cikrle, Petr (advisor)
This project solves the creation of calibration relations for determining the compressive strength of early age concrete. It deals with news in the field of hardness methods. 36 samples were made for this experiment and tested by ultrasound and by impact hammer SilverSchmidt type L with Mushroom Plunger. The result is set of calibration relations for determining of compressive strength for different methods and their combinations.
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Stochastic Prediction of Mean Monthly Flows in Selected Hydrometric Profile
Jansa, Jakub ; Menšík, Pavel (referee) ; Marton, Daniel (advisor)
The diploma thesis is focused on the average monthly flows forecast in the selected hydrometric profile. Aim of this work will be evaluation of the calculated values and the interpretation of the results in understandable form. The next step will be find an appropriate connection between randomly-generated inputs in the form of random real flow series using the standard hydrological prediction models. This models are based on the principles of artificial intelligence and probability model. The result of the work will be verification of procedures and compilation of mean monthly flow stochastic forecast in selected hydrometric profile, which would be used for a reservoirs management, respectively for water systems management.
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Calibration of indirect methods for maesurement of properties of alkali activated concretes
Vrba, Pavel ; Kocáb, Dalibor (referee) ; Bílek, Vlastimil (advisor)
This work solves creation of calibration relations to determine cube compressive strength, dynamic and static elastic modulus of alkali-activated concrete by non-destructive methods. Alkali-activated concrete is spoken of as a new material used in civil engineering. It shows different properties than normal concrete based on Portland cement. That's why the modification of common calibration relation seems necessary. Fresh concrete was made in the concrete plan ŽPSV a.s., Uherský Ostroh in three mixtures and always in the number of 18 cubes and 3 prisms. The samples were tested by impact hammer Schmidt type L, type N, SilverSchmidt PC-N and by ultrasound in 6 time periods of three specimens. After that, the cube compressive strength was determined. Status of static elastic modulus was determined in a time period of 28 days. The results are calibration relations to determine the progress of compressive strength and modulus of elasticity for each method and their combination.
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Relation Between River Flows and Suspended Sediments in the Selected Hydrometric Profile of the Thaya River Basin
Bobková, Dominika ; Menšík, Pavel (referee) ; Marton, Daniel (advisor)
The issue of the sediments of their transport and subsequent storage in water basins is an important topic which is perceived very seriously by the water management expert public. Therefore, work in this area is very desirable. The aim of bachelor‘s work is to find and estimate possible dependencies between average daily discharge and average daily values of non dissolved substances carried in suspension. The dependencies will serve as a partial basis for addressing the ATCZ28 SEDECO Sediments project, ecosystem services and interrelation with floods and droughts in the AT-CZ Border region. The data are analysed in different periods of time. The result of the analysis is the trend line regulations and the degree of dependence between flows and concentrations, which is expressed by means of a coefficient of determination. The practical application is performed on data measured in the Trávní Dvůr profile on the Dyje river for the years 1996 and 1997.
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Long Term Discharge Prediction in River Hydrometric Profile
Šelepa, Milan ; Menšík, Pavel (referee) ; Marton, Daniel (advisor)
The diploma thesis is focused on the long term prediction of mean monthly flows in hydrometric profile for purposes of reservoir control optimization and optimization of reservoir systems. Discharges were predicted using by artificial neural network method. Predicted flows were statistically evaluated by relevant coefficients and then compared with the measured flows for given river hydrometric profiles.
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Regression goodness-of-fit criteria according to dependent variable type
Šimsa, Filip ; Hanzák, Tomáš (advisor) ; Hlubinka, Daniel (referee)
This work is devoted to the description of linear, logistic, ordinal and multinominal regression models and interpretation of its parameters. Then it introduces a variety of quality indicators of mathematical models and the re- lations between them. It focuses mainly on the Gini coefficient and the coefficient of determination R2 . The first mentioned is established by modifying the Lorenz curve for ordinal and continuous variables and by comparing the estimated proba- bilities for nominal variable. The coefficient of determination R2 is newly defined for the nominal variable and is examined its relationship with Gini coefficient. As- suming normally distributed scores and errors of the model is numerically derived the relation between the Gini coefficient and the coefficient of determiantion for different distribution of continuous dependent variable. Theoretical calculations and definitions are illustrated on two real data sets. 1
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Estimation and goodness-of-fit criteria in logistic regression model
Ondrušková, Markéta ; Hanzák, Tomáš (advisor) ; Zvára, Karel (referee)
In this bachelor thesis we describe binary logistic regression model and estimation of model's parameters by maximum likelihood method. Then we propose algorithm for the least squares method. In the goodness-of-fit criteria part we define Lorenz curve, Gini coefficient, C-statistics, Kolmogorov-Smirnov statistics and coefficient of determination R2 . We derive their relation to different sample coefficients of correlation. We derive typical relation between Gini coeffi- cient, Kolmogorov-Smirnov statistics and newly also coefficient of determination R2 via model of normally distributed score of bad and good clients. These derived teoretical results are verified on three real data sets. Keywords: Binary logistic regression, maximum likelihood, ordinary least squa- res, Gini coefficient, coefficient of determination. 1
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Dependency of Asphalt Mixtures Low Temperature Properties on Binder Properties
Veselý, Petr
The paper deals with results of tests for low temperature properties of asphalt mixtures in correlation with results of tests on low temperature properties of the bitumen used in those. Properties of materials used in temperatures, which with changing climate keep approaching the critical value, are still very current topic, which cannot be overlooked. The aim of this paper is to point out the extent in which we can affect these properties with different binders. For this purpose, low temperature tests were carried out which include the thermal stress restrained specimen test to set critical temperature of asphalt mixture, Fraasse breaking point and the bending beam rheometer.
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Description of Relation between Flow and Suspended Sediment Load in a Hydromertic Profiles of a Selected Rivers
Bobková, Dominika ; Janál,, Petr (referee) ; Marton, Daniel (advisor)
The issue of the relationship between water discharge and the suspended sediment loads is a globally highly addressed topic. Knowing the suspended sediment loads in the streams avoids problems with over-filling of water cannons and thus prevents insufficient capacity of water reservoirs. This thesis is partly a follow-up to the bachelor thesis, which extends and introduces new procedures. Neural networks, more specifically multilayer perceptron neural networks, are used to analyse the relationship between water discharge and suspended sediment loads. The results of the networks are then processed in Excel into graphs and evaluated using the coefficient of determination, Nash-Sutcliffe coefficient and RMSE coefficient. The practical application is solved on two profiles - the profile Podhradí nad Dyjí and the profile Židlochovice. Each profile is examined in a different period.
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