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Cluster point processes in insurance mathematics
Veselá, Veronika ; Pawlas, Zbyněk (advisor) ; Dostál, Petr (referee)
Title: Cluster point processes in insurance mathematics Author: Veronika Veselá Department: Department of Probability and Mathematical Statistics Supervisor: RNDr. Zbyněk Pawlas, Ph.D. Abstract: In the present work we study point processes and their importance in insurance mathematics. With the help of cluster and marked point processes we can describe a model that considers times of claim occurence and times and hei- ghts of corresponding payments. We study two specific models which can be used to predict how much money is needed for claims which happened. The first model is chain ladder in the form of Mack's model. For this model we show chain ladder estimators of development factors, estimates of their variance and their proper- ties. We try to find one-step ahead prediction and multi-step ahead prediction, which we use for calculating prediction of reserves. We shortly review asymptotic properties of the estimators in Mack's model. The second model is the Poisson cluster model. Firstly we define this model and the variables entering the model. Then we devote attention to one-step ahead and multi-step ahead prediction. We also study prediction when some variables have specific distributions. Finally, we use both methods of prediction on simulated data and compare their average relative absolute errors....
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Modifications of stochastic objects
Kadlec, Karel ; Štěpán, Josef (advisor) ; Dostál, Petr (referee)
In this thesis, we are concerned with the modifications of the stochastic processes and the random probability measures. First chapter is devoted to modifications of the stochastic process to the space of continuous functions, modifications of submartingale to the set of right-continuous with finite left-hand limits functions and separable modifications of stochastic process. In the second chapter is the attention on the regularization of random probability measure in Markov kernel focused. In particular, we work with random probability measures on the Borel subset of the Polish space, or Radon separable topological space.
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Teaching of science based on activity of students at lower secondary education
Žáčková, Tereza ; Pavlasová, Lenka (referee) ; Dostál, Petr (referee)
The topic of this thesis is use of a kind of activity-based teaching in biology lessons in lower secondary school. The thesis is made up of two main parts. The first theoretical part deals with history, characteristic and structure of class work activity learning, its role in school documents, teaching methods and organizational forms of teaching supporting class work activity learning in biology lessons. Another part of the theoretical part is fundamentals in biology lessons that teacher should abide by regardless of the type of teaching. The theoretical part contains a part which deals with presentations in Microsoft PowerPoint and their definition in educational process. The purpose of the experimental part based on a questionnaire for teachers of biology is to find out important facts and the answers to the questions which follow from the nature of the research, and additionally to verify stated hypothesises of the research. The research focuses on teachers of biology at lower secondary school in schools situated in Prague and central Bohemia. Key words: activity-based teaching, teaching methods and organizational forms supporting activity-based teaching
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Warehouse hall with administration
Dostál, Petr ; Kovařík, Lukáš (referee) ; Brukner, Bohuslav (advisor)
The content of this diploma thesis is the design of a new warehouse hall with administration in the Zetor complex in the Brno – Líšeň district. It is the building thaht is divided into warehouse hall and administrative part. The warehouse hall has one floor and will be used for storage of steel products within the Zetor complex. The administrative part has three floors, where the 1st floor serves as a background for warehouse employees, on the 2nd and 3rd floors there are office space with social facilities. The construction is based on deep foundations on embossed piles. The supporting structure of the building is designed as a prefibricated reinforces concrete skeleton with continuous columns and beams places on the columns. The peripheral shell of the both part sis made of sandwich mineral panels. The supporting structure of the roof of the warehouse hall consists of roof trusses and is made as a flat single-skin. The ceiling construction of the administrative part is made of SPIROLL ceiling panels, the roof of the administration is also made as a flat single-skin.
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Expert System for Decision-Making on Stock Markets Using Investor Sentiment
Janková, Zuzana ; Lenort, Radim (referee) ; Zinecker, Marek (referee) ; Chramcov, Bronislav (referee) ; Dostál, Petr (advisor)
The presented dissertation examines the potential of using the sentiment score extracted from textual data with historical stock index data to improve the performance of stock market prediction through the created model of the expert system. Given the large number of financial-related text documents published by both professional and amateur investors, not only on online social networks that could have an impact on real stock markets, but it is also crucial to analyze and in particular extract financial texts published by different users. investor sentiment. In this work, investor sentiment is obtained from online financial reports and contributions published on the financial social platform StockTwits. Sentiment scores are determined using a hybrid approach combining machine learning models with the teacher and neural networks, with multiple lexicons of positive and negative words used to classify sentiment polarity. The influence of sentiment score on the stock market through causality, cointegration and coherence is analyzed. The dissertation proposes a model of an expert system based on fuzzy logic methods. Fuzzy logic provides remarkable features when working with vague, inaccurate or unclear data and is able to deal with the chaotic environment of stock markets. In recent scientific studies, it has gained in popularity a higher level of fuzzy logic, which is referred to as type-2 fuzzy logic. Unlike the classic type-1 fuzzy logic, this higher type is able to integrate a certain level of uncertainty between the dual membership functions. However, this type of expert system is considerably neglected in the subject issue of stock market prediction using the extracted investor sentiment. For this reason, the dissertation examines the potential to use and the performance of type-2 fuzzy logic. Specifically, several type-2 fuzzy models are created. which are trained on historical stock index data and sentiment scores extracted from text data for the period 2018-2020. The created models are assessed to measure the prediction performance without sentiment and with the integration of investor sentiment. Subsequently, based on the created expert model, the investment strategy is determined, and its profitability is monitored. The prediction performance of fuzzy models is compared with the performance of several comparison models, including SVM, KNN, naive Bayes and others. It has been observed from experiments that fuzzy logic models are able to improve prediction by appropriate setting of membership and uncertainty functions contained in them and are able to compete with classical expert prediction models, which are standardly used in research studies. The created model should serve as a tool to support investment decisions for individual investors.
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Risk of Choosing a Supplier Using Fuzzy Logic
Vyskočilová, Monika ; Janková, Zuzana (referee) ; Dostál, Petr (advisor)
The thesis deals with the design of a model used for evaluation and selection of fire-retardant footwear suppliers for the company Požární bezpečnost s. r. o. The thesis includes a summary of the theoretical foundation for processing the work, a presentation of the selected company and a draft of an evaluation model that assesses the contractor based on the chosen criteria and makes it easier for the company to make their decision. The model is created by using fuzzy logic in Microsoft Excel and MATLAB programs.
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Using Artificial Intelligence to Reduce Risk in a Company
Friedl, Pavel ; Šebestová, Monika (referee) ; Dostál, Petr (advisor)
Presented diploma thesis is focused on evaluation of the supplier’s risk and the selection of the most suitable supplier with the use of artificial intelligence. The main part of the diploma thesis deals with the creation of the decision models. The decision models will be created in MS Excel and MATLAB based on the rules of the fuzzy logic. These models will determine the most suitable supplier for the company expert Elektro GOLA s.r.o. and they will also evaluate the supplier’s risk.
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Evaluation of Supllier Risk Using Fuzzy Logic
Lázniček, Matěj ; Janková, Zuzana (referee) ; Dostál, Petr (advisor)
This diploma thesis deals with the evaluation of supplier risk for a chosen company Vinařství Soška using the fuzzy logic principles. This company like many others is forced to shift its sales to the Internet environment due to the government restrictions established to reflect the pandemic situation. For a successful Internet business, it is necessary to choose an optimal ecommerce software based on the company requirements. For this purpose, two fuzzy logic models are built in Microsoft Excel and MATLAB software. Their aim is to evaluate the potential risk of all of the suppliers. Based on this evaluation, the results are transformed into specific recommendations on how to choose the optimal solution for the company. The first chapters deal with the general theory that is later used in the analytical part.
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Population dynamics of Minuartia smejkalii
Hrušková, Karolína ; Münzbergová, Zuzana (advisor) ; Dostál, Petr (referee)
Serpentine areas in the Czech Republic form minor but important islands in the landscape with specific chemical properties such as high content of magnesium and other heavy metals. Due to this, serpentine is toxic for most plants. Increased demands on the survival and occurrence of plants lead to the emergence of serpentine specialists obligatorily specialized in these extreme habitats. Currently, serpentine areas are threatened by gradual overgrowth of sites, insufficient or poor site management and fragmentation or shrinkage of sites due to anthropogenic activities. Along with the disappearing localities, the serpentine specialists, are becoming highly endangered. Minuartia smejkalii is highly endangered serpentine specialist with an endemic occurrence in the Czech Republic with great need of its conservation. The aim of the work was to collect data on population dynamics of the species and identify habitat and climatic factors affecting population growth. We studied dynamics in all existing 7 populations during the period from 2006 to 2020 were collected. We linked these data to information on population dynamics, habitat and climatic factors and analysed them using Integral projection models (IPM). The study presents the importance of individual habitat and climatic conditions on the dynamics...
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