National Repository of Grey Literature 47 records found  1 - 10nextend  jump to record: Search took 0.01 seconds. 
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.
Detection of Pilot Inattention
Novotný, Josef ; Mekyska, Jiří (referee) ; Smékal, Zdeněk (advisor)
This master thesis deals with the issue of pilot inattention and proposes a design of a system for detecting inattention of general aviation pilots. Inattention belongs to one of the human-caused errors that currently contribute to the most common causes of aviation accidents. The theoretical part deals with the definition of inattention, compares different aviation categories based on flight rules, and contains a search of detection methods. The practical part of the work deals with the selection of suitable sensors, data collection, and implementation of detection algorithms. In this thesis, two different approaches were chosen. The first implementing machine learning using the RUSBoost classifier, which detects states of attention and distraction. The second approach represents the design of a system for detecting pilot inattention based on a set of rules specified in the CLIPS expert system.
Creating a knowledge base for insurance products
Pokorný, David ; Štrof, Jan (referee) ; Jirsík, Václav (advisor)
This bachelor thesis is about developing a knowledge base for an expert system. Knowledge base is a set of appropriately coded knowledge from the areas of human activities, which can be expressed with some uncertainty. This created knowledge base is used for qualified selection of appropriate risk life insurance. Base is being create in cooperation with financially – advisory company and will be deployed in regular service where it will help Sales representatives in their regular expert work. Theoretical part of the document describes problematics of creation and tuning of a knowledge base, there is also described a wide range of usage expert system aplications and illustration of NPS expert system and its syntax. Practical part then consists of description of development knowledge base, evaluation of the final results and proposals for another development.
Product filtering personalization via knowledge systems for e-shops
Korčák, Aleš ; Petyovský, Petr (referee) ; Jirsík, Václav (advisor)
The bachelor's thesis deals with the concept and implementation of an application for personalizing product filtering, a web module that allows the answering of questions and the concept and implementation of a knowledge base that sets the parameters of the filter.
Creating a knowledge base for the diagnosing of diseases
Macháček, Daniel ; Steinerová, Kateřina (referee) ; Jirsík, Václav (advisor)
This bachelor thesis is focused on problematic of creation knowledge base. It is describing basics of expert systems, their function and possible usage in modern world. In result of this thesis is knowlenge base in web aplication NPS able to diagnose diseases of hematology-oncology and that is proving possibility for use in real life. Knowledge base was created in cooperation with experts in the medical field and contains real data.
Scheduling System in Healthcare
Janíčková, Natália ; Kolářová, Jana (referee) ; Sekora, Jiří (advisor)
The Bachelor thesis is dedicated to expert scheduling systems in healthcare. The thesis describes all parts of system design: algorithm, software tools used in a process, and the developed application itself. The system developed in this thesis generates a schedule of the services that respect requirements given by law, employer, and also employees in the healthcare organizations. Application outputs involve basic overviews for employees and employers.
User interface for an expert system
Kořínek, Lukáš ; Boštík, Ondřej (referee) ; Jirsík, Václav (advisor)
This bachelor's thesis is about design and implementation of an expert system user interface. Concerned system is a universal rule-based diagnostic expert system called NPS, which has been developed at FEEC BUT. The interface has been created as a bilingual web application based on modern technologies, which might bring the opportunity to reach variety of devices and a broad user audience. It also enhances the system with means of user authorization, history browsing, user management, knowledge management and more. The application runs on faculty's infrastructure and is undergoing active testing by both physical users and automated tests. Theoretical part of the document describes knowledge and expert system problematics, followed by properties of the NPS system and discussion about web technologies (actual trends in the field, client to server communication, testing strategies and security). Practical part then consists of created interface overview, system architecture description, implementation details, testing and steps used to deploy the application on faculty's network infrastructure.
Practical use of knowledge systems in automotive diagnostics
Koláček, Miroslav ; Pudil, Pavel (advisor) ; Novák, Michal (referee)
This thesis in its theoretical part summarizes international knowledge of the problematics of expert systems and their application in automotive diagnostics. In the practical part it solves the methodology and selection of appropriate expert system for the development of diagnostic application. This issue is further elaborated by the methodology of an expert´s knowledge transfer into the knowledge database and creating application for its use within the Windows, Web and Android platforms. Beside the working out the product itself it also provides instructions for others who are interested in preparing similar applications and topic for the future development of the already prepared tool.
Conceptual Structures As a Tool for Knowledge Representation
Ferbarová, Gabriela ; Ivánek, Jiří (advisor) ; Souček, Martin (referee)
(in English): Conceptual graphs are a formal knowledge representation language introduced by John F. Sowa, an American specialist on Artificial Intelligence, at the end of the seventies. They are the synthesis of heuristic and formalistic approach to Artificial Intelligence and knowledge procession. They provide meaning and knowledge in form, which is logically precise, human- readable and untestable, and it is applicable in the computing domain in general. Conceptual graphs can be expressed through a first-order logic, which makes them a quality tool for intelligent reasoning. Their notation CGIF was standardised by norm ISO/IEC 24707:2007 as one of the three dialects of Common logic, which frames the set of logic based on logic. Conceptual graphs are also mappable to knowledge representation languages standardised for the Semantic Web; OWL and RDF (S). This work introduces the conceptual graph theory in the context of scientific fields like linguistics, logic and artificial intelligence. It represents the formalism proposed by John F. Sowa and some extensions that have emerged over the past decades, along with the need for improvements to the representational properties of graphs. Finally, the work provides an illustrative overview of the implementation and use of conceptual graphs in practice....
Agent for playing Texas Hold'em poker
Bambušek, Petr ; Blažek, Jan (advisor) ; Majerech, Vladan (referee)
Main purpose of this thesis is to create agent for playing Texas Hold'em poker, which will be easily extensible by new inputs, outputs and game strategies. We present this firstly on input based on image recognition of client of chosen online poker site, secondly on simple game strategy based on expert system. Main working algorithm of agent will be encapsulated in single object and will run in separate thread. This will allow us to easily incorporate and manage agent from another programs, example way of managing and setting is presented on simple graphical application. The resulting agent can be further used as tool for testing and creation of new game strategies. Powered by TCPDF (www.tcpdf.org)

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