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Methodology for predictive mapping of rare and endangered bryophytes distribution in the Czech Republic
Man, Matěj ; Wild, Jan
The methodology introduced certified procedure of using species distribution modelling to support discovery of new localities with presence of rare species of bryophytes and lichens in Czech Republic. The procedure available for general public, it provides algorithms, computation power and environmental data. User provides training data – coordinates of species presence. From the software interface it is also possible to request the coordinates directly from Database of Lichens and Bryophytes (DaLiBor). Georeferenced map is the output form the software. The aim of the methodology is to provide integrated tool for conservation planning and research to promote the bryological and lichenological field survey in Czech Republic. The methodology will help to focus the survey which could make the survey more efficient and cheaper according to money but also human resources. The methodology is based exclusively on free software, mostly open source and free licence. In the Czech Republic, the methodology provides modern software approach to target botanical research. In national practical nature conservation, it is all new application of established procedure from other fields.\n
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Lightning activity prediction using a numerical weather prediction model
Uhlířová, Iva ; Popová, Jana (advisor) ; Zacharov, Petr (referee)
Lightning activity is considered a severe meteorological hazard that needs to be studied, monitored as well as predicted. This thesis focuses on the prediction of lightning activity by the Lightning Potential Index (LPI) in the COSMO numerical weather prediction (NWP) model that comprises 1- and 2-moment (1M and 2M, respectively) cloud microphysical schemes. The objective of this thesis is to investigate the correlation between the predicted lightning activity and the detected one (by the European network for lightning detection EUCLID). Events of the years 2018 and 2019 that recorded significant lightning activity over Czechia are considered for the analyses. For the first time over Czech region, the prognostic values of LPI calculated for each event are verified. In particular, the spatio- temporal distribution of the predicted vs. detected lightning activity is evaluated. Both spatial characterizations and diurnal course of detected lightning activity correspond well to the theoretical knowledge. Thus, spatial (horizontal) and temporal approaches are applied to verify the lightning activity prediction. The results of this thesis successfully verify the LPI prognostic values both in space by comparing the LPI values with the proximity of detected lightning flashes, and in time by contrasting the...
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The Use of Artificial Intelligence on Stock Market
Kuna, Martin ; Veselý, Karel (referee) ; Dostál, Petr (advisor)
Diplomová práce se zabývá aplikací vybraných metod umělé inteligence v prostředí kapitálových, potažmo akciových, trhů. Konkrétně se zaměřuje na využití umělých neuronových sítí pro predikci trendu a na možnost aplikace genetických algoritmů k řešení problému optimalizace investičního portfolia. Obsahuje návrh řešení uvedených problémů v praxi. Návrhy jsou koncipovány ve formě modelů zpracovaných ve vývojovém prostředí Matlab.
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The analysis of biochemical and hematological data in athletes
Molnárová, Monika ; Korvas, Pavel (referee) ; Chlíbková, Daniela (advisor)
This thesis is focused on patophysiology changes in organism of ultramaraton runners. It analyze the blood parameters idnicating patological changes. It describes the principles of analysis and laboratory testing not only in laboratories, but also in terrain conditions. The thesis includes statistical testing and evaluation of hematological and biochemical parameters indicating severe patologies. With the use of Spearman correlation coefficient are determined the relations between the parameters. The relation between the found parameters are then further analyzed by regression. The goal of the thesis is finding a way to predict biological parameters by using a group of other parameters. In the practical part of the work is described the algorithm for prediction, the network testing results and other ways to improve the prediction algorithm.
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Mixing of Predictors in Parameter Estimation
Podlesna, Yana ; Kárný, Miroslav
This bachelor thesis deals with the design of the method for solving the curse of dimensionality arising in the quantitative modeling of complex interconnected systems. The employed predictive models are based on a discrete Markov process. Prediction is based on estimating model parameters using Bayesian statistics. This work contains method for reducing the amount of data needed for prediction in systems with a large number of occurring states and actions. Instead of estimating a predictor dependent on all parameters, the method assumes the use of several predictors, which arise from estimating parametric models based on dependences on different regressors. The behavioral properties of the proposed method are illustrated by simulation experiments.
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Driver Steering Model for Simulation Algorithms
Tmejová, Tereza ; Zháňal, Lubor (referee) ; Hejtmánek, Petr (advisor)
This diploma thesis deals with the creation of a computation driver model. In the first part, there is an overview on driver models for longitudinal and lateral control. Next, driving maneuvres that could be selected for testing of driver model are described. In the practical part, there is created a computational driver model, whose task is to follow required path. The resulting model is tested on three driving maneuvers - steady turning, moose test and slalom. Finally, this model is tested on the passage of a real track. For all these tracks, a comparison is made and the success of the model is evaluated.
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Prediction of the Effect of Mutation on Protein Solubility
Velecký, Jan ; Martínek, Tomáš (referee) ; Hon, Jiří (advisor)
The goal of the thesis is to create a predictor of the effect of a mutation on protein solubility given its initial 3D structure. Protein solubility prediction is a bioinformatics problem which is still considered unsolved. Especially a prediction using a 3D structure has not gained much attention yet. A relevant knowledge about proteins, protein solubility and existing predictors is included in the text. The principle of the designed predictor is inspired by the Surface Patches article and therefore it also aims to validate the results achieved by its authors. The designed tool uses changes of positive regions of the electric potential above the protein's surface to make a prediction. The tool has been successfully implemented and series of computationally expensive experiments have been performed. It was shown that the electric potential, hence the predictor itself too, can be successfully used just for a limited set of proteins. On top of that, the method used in the article correlates with a much simpler variable - the protein's net charge.
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Intelligent Manager of Fantasy Premier League Game
Vasilišin, Maroš ; Burgetová, Ivana (referee) ; Hynek, Jiří (advisor)
Hra Fantasy Premier League poskytuje miliónom hráčov po celom svete možnosť stať sa na chvíľu manažérom svojho vlastného klubu. Výsledky a bodové ohodnotenie v hre závisia na správnom predvídaní, ako sa budú hráči chovať v skutočných futbalových zápasoch. Ak by pri tomto rozhodovaní pomáhal software na predikciu a analýzu budúcich výkonov hráčov, výsledky v hre sa môžu rapídne zlepšiť. Táto diplomová práca sa zaoberá návrhom a implementáciou predikčného modelu, ktorý využíva neurónové siete na predikcie časových radov počas celej sezóny v hre. Boli použité metódy na spracovanie dát o hráčoch a kluboch za posledné 4 sezóny. Výkonnosť a presnosť predikčných metód boli testované na dátach z poslednej sezóny Premier League a predikcie algoritmu sa vo väčšine prípadov blížili realite. Ak by sa užívateľ držal predikčného modelu v hre stopercentne, získal by väčší počet bodov ako bežný hráč, ktorý žiadny predikčný model nepoužíva.
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Prediction of the Effect of Mutation on Protein Solubility
Marko, Július ; Smatana, Stanislav (referee) ; Hon, Jiří (advisor)
Protein solubility is a key problem in production of functional proteins. Prediction of the effect of mutation on protein solubility could save a lot of time and money, as it would provide in silico prediction of solubility enhancing mutations before performing deep mutational scanning in laboratory. In this work, new predictor of the effect of mutation on protein solubility SoluProtMut is introduced that is based on machine learning methods. Most of the existing predictors predict the effect from the amino acid sequence. In addition to the sequence, the tool presented in this work also uses the spatial structure of the protein, which can significantly increase it's accuracy.
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Optimization of Run Configurations of k-Wave Jobs
Sasák, Tomáš ; Jaroš, Marta (referee) ; Jaroš, Jiří (advisor)
This thesis focuses on scheduling, i.e. correct approximation of configurations used to run k-Wave simulations on supercomputers from the IT4Innovations infrastructure. Especially, for clusters Salomon and Anselm. A single work is composed of a set which contains many simulations. Every simulation is executed by some code from the k-Wave toolbox. To calculate the simulation, it is necesarry to select a suitable configuration, which means the amount of supercomputer resources (number of nodes, i.e. cores), and the duration of the rental. Creation of an ideal configuration is complicated and is even harder for an inexperienced user. The approximation is made based on the empiric data, obtained from multiple executions of different sets of simulations on given clusters. This data is stored and used by a set of approximators, which performs the actual approximation by methods of interpolation and regression. The text describes the implementation of the final scheduler. By experimenting, the most efficient methods for this problem has found out to be Akima spline, PCHIP interpolation and cubic spline. The main contribution of this work is creation of a tool which can find suitable configuration for k-Wave simulation without knowing the code or having lots of experience with its usage.
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