|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
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.
|
|
|
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...
|
|
|
Algorithmization for decision support
Strečková, Nikola ; Budík, Jan (referee) ; Dostál, Petr (advisor)
This thesis is focused on understanding investment strategies on cryptocurrency markets and thanks to the own algorithm create an automated program to support the decision making. To deploy and develop the algorithm is used MetaTrader5 platform, which uses the MQL5 programming language. The strategy was backtested on historical data of BTCUSD and BTCEUR to validate the efficiency of the strategy.
|
|
| |
|
|
The Use of Artificial Intelligence for Decision Making in the Firm
Šlemenda, David ; Budík, Jan (referee) ; Dostál, Petr (advisor)
Diploma thesis deals with the creation of an automated trading system for foreign exchange market with the usage of artificial intelligence and elements of technical analysis. In the custom solution design a brokerage company for trading and backtesting is selected with the help of fuzzy logic. For selecting currency pairs for backtesting the strategy on is used method of clustering called self-organizing map. The particular ATS is created in MetaTrader4 platform with the usage of a programming language MQL4 and a FANN library for creating artificial neural networks.
|
|
|
The Application of Fuzzy Logic for Evaluation of Quality of Customers
Behancová, Katarína ; Janková, Zuzana (referee) ; Dostál, Petr (advisor)
The diploma thesis deals with the evaluation of the quality of customers using fuzzy logic based on the evaluation of their orders. The thesis consists of three parts. The first part is the theoretical basis of the thesis, which explains the issue of fuzzy logic. The second is the analytical part, in which the company ZKN METAL s.r.o. was introduced, for which a specific solution is subsequently proposed in the third and last part of the thesis. This solution is processed in the form of two models. The first of the models is processed in the MS Excel program and the second is modeled using the MATLAB programming environment. Both models are set in a user-intuitive environment and they are compared with each other afterwards.
|
guest ::
RSS feed.