Grabusts, Pēteris

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Preferred name
Grabusts, Pēteris
Official Name
Grabusts, Pēteris
Alternative Name
Peter Grabusts
Pēteris Grabusts
Main Affiliation
Email
peteris.grabusts@rta.lv
Scopus Author ID
55835004700
Researcher ID
AAU-5594-2021

Research Output

Now showing 1 - 10 of 72
  • Publication
    Construction Methods of the Decision Trees for Genetic Programming
    (2008)
    Grabusts, Pēteris 
    Mūsdienās ģenētiskās programmēšanas iespējas tiek plaši izmantotas daudzos optimizācijas un klasifikācijas uzdevumos. Lai ģenētiskās programmēšanas metodes varētu tikt veiksmīgi pielietotas, ir nepieciešams konstruēt attiecīgus lēmumu kokus. Lēmumu koki un likumi uz to pamata ir intelektuālās datu analīzes sastāvdaļa un veiksmīgi tiek pielietoti klasifikācijas problēmu risināšanā. Pastāv vesela virkne dažādu paņēmienu, kas dod iespēju konstruēt lēmumu kokus ģenētiskās programmēšanas iespēju izmantošanai. Literatūras analīze liecina, ka optimālākā metode lēmumu koku konstruēšanā sastāv no diviem etapiem. Sākotnēji tiek veidots lēmumu koks, izmantojot C4.5 algoritmu, kas turpmāk tiek izvērsts ar ģenētiskās programmēšanas operatoru palīdzību. Šajā gadījumā ģenētiskā programmēšana tiek lietota kā globāla meklēšanas stratēģija precīza lēmumu koka atrašanā. Rakstā analizētas mūsdienu pieejas lēmumu koku konstruēšanā un izskatītas ģenētiskās programmēšanas iespējas, kas tiks izmantotas turpmākajā pētnieciskajā darbībā.
  • Publication
    CREATION OF INNOVATIVE APPROACH FOR STUDY OF THE NATIONAL FISCAL SPACE
    (2017)
    Ērika Žubule
    ;
    Grabusts, Pēteris 
    ;
    Lūcija Kavale
    The choice and topicality of the theme is substantiated by the fact that a sustainable development of a country is affected by the policy implemented by the government. One of its main parts is the fiscal or budget policy which means the formation of the necessary funds of the revenues and expenditures to ensure the functioning of the government. Accordingly, the concept of fiscal space has been activated which is closely connected with the implementation of the instruments of fiscal policy (taxes, government expenditures, government debt). The aim of the research is to create an innovative approach to the investigation of the creation of the state fiscal space applying the simulation method in the environment of Matlab/Simulink in order to forecast the influence of the corporate income tax on the state economic and financial indicators taking into account the changes of the corporate income tax offered by the government and the Bank of Latvia. Methodology of the research implies the following activities: the identification of the concept of fiscal space and its application in the context of the influence on economy; the creation of the assessment methodology of the components of fiscal space using technological tools (data modelling in Matlab / Simulink environment).
    Scopus© Citations 1
  • Publication
    POTENTIAL FUNCTION METHOD APPROACH TO PATTERN RECOGNITION APPLICATIONS
    (2017)
    Grabusts, Pēteris 
    Potential function method was originally offered to solve the pattern recognition tasks, then it was generalized to a wider range of tasks, which were associated with the function approximation. Potential function method algorithms are based on the hypothesis of the nature of the function that separates sets according to different classes of patterns. Geometrical interpretation of pattern recognition task includes display of patterns in the form of vector in the space of input signal that allows to perceive the learning as approximation task. The paper describes the essence of potential function method and the learning procedure is shown that is based on practical application of potential methods. Pattern recognition applications with the help of examples of potential functions and company bankruptcy data analysis with the help of potential functions are given.
    Scopus© Citations 5
  • Publication
    IMPACT OF PARAMETERS CHARACTERIZING CLUSTERING ON DATA ANALYSIS RESULTS
    (2012)
    Grabusts, Pēteris 
    Clustering algorithms are used to group some given objects defined by a set of numerical properties in such a way that the objects within a group are more similar than the objects in different groups. All clustering algorithms have common parameters the choice of which characterizes the effectiveness of clustering. The most important parameters characterizing clustering are: metrics (the distance between cluster elements and cluster centre), number of clusters k and cluster validity criteria. The goal of the paper – to perform the evaluation of the validity of metrics’ choice, to describe the change with respect to the number of clusters for experimental data purposes and to evaluate the credibility of clustering results. As an input data the table describing the rating of Latvian state higher educational institutions for year 2011 has been used and the goal of the experiment was to show, how by using the clustering methods it is possible to analyze the mentioned data in an alternative way.
  • Publication
    Evaluation of Clustering Results in the Aspect of Information Theory
    (2020)
    Grabusts, Pēteris 
    Clustering is the process of finding possible groups in a given set, taking into account the signs of similarity or difference between the elements of this set. In cluster analysis, it is necessary to classify the data in some way or to find regularities in given data, therefore the concept of “regularity” is gaining more and more importance in the context of intelligent data processing systems. It is necessary to find out how the data are related to each other, what is the similarity or difference of different data, what is the measure of comparison of these data. For such purposes, various clustering algorithms can be used, which divide the data into groups according to certain criteria - metrics. Metric in this context means the distance between the points in the cluster. The existing methods of entropy clustering is an information-theoretical approach to the problem of clustering. In the work the evaluation of clustering quality was performed with the help of clustering quality criteria and in the context of information theory concepts.
  • Publication
    ANALYSIS AND EVALUATION OF FISCAL POLICY IN LATVIA
    (2019)
    Erika Zubule
    ;
    Grabusts, Pēteris 
    The choice and topicality of the research topic is based on the fact that upon strengthening of the government's regulating role in economy, the notion of public finances positions itself, and state budget has become an important subject of both economic and political discussions as implementation of fiscal policy is takes place through it. In order to evaluate fiscal policy, it is necessary to evaluate the potential influence of different fiscal policy instruments on social and economic situation in the state. Aim of the research – to evaluate activities of fiscal policy implemented in Latvia in context of certain tax, namely, influence of corporate income tax on state's economic and financial indicators, identifying the main risks and imperfections of fiscal policy when ensuring state's budget. Applying simulation methods in the environment of Matlab/Simulink, the authors analyze and evaluate the influence of fiscal decisions and their implementation on the situation in Latvia, analyzing the most important tendencies in the sphere of corporate income tax payments according to the tax reform commenced in 2018.
  • Publication
    Analysis of Fuzzy Time Series Forecasting for Migration Flows
    (2022)
    Oleg Uzhga-Rebrov
    ;
    Grabusts, Pēteris 
    The goal of this article is to forecast migration flows in Latvia. In comparison with many other countries with sufficiently symmetric emigration and immigration flows, in Latvia, migration flows are very asymmetric: the number of emigrants considerably exceed the number of immigrants. Since statistical data about migration are usually inaccurate, we employ fuzzy time series forecasting methods for prognosticating migration flows in Latvia forecasting. The use of this type of method is often useful not only for forecasting purposes. Three different methods for fuzzy time series forecasting are used. A detailed comparative analysis of the obtained results is given. Generalized forecasts of the expected net migration flow in the future are presented.
  • Publication
    The Choice of Metrics for Clustering Algorithms
    (2011)
    Grabusts, Pēteris 
    Methods of data analysis and automatic processing are treated as knowledge discovery. In many cases it is necessary to classify data in some way or find regularities in the data. That is why the notion of similarity is becoming more and more important in the context of intelligent data processing systems. It is frequently required to ascertain how the data are interrelated, how various data differ or agree with each other, and what the measure of their comparison is. An important part in detection of similarity in clustering algorithms plays the accuracy in the choice of metrics and the correctness of the clustering algorithms operation.
    Scopus© Citations 25
  • Publication
    POSSIBILITIES OF SIMULATION MODELS VISUALIZATION IN TEACHING PROCESS
    (2016)
    Grabusts, Pēteris 
    Teaching experience shows that during educational process student perceive graphical information better than analytical relationships. Many educational courses operate with models that were previously available only in mathematics and physics disciplines. As a possible solution, there could be the use of package Matlab Simulink in realization of different algorithms both for engineering disciplines and economic studies. The paper presents examples of using simulation modelling in the educational research processes.
  • Publication
    Niskanen Classical Model Implementation of the Office’s Operations Evaluation
    (2015)
    Ērika Žubule
    ;
    Grabusts, Pēteris 
    The economic downturn has caused fiscal tension in the country in recent years. Budget revenues decreased and it indicated the need for the revision and control of expenditure. Therefore, the issues related to the evaluation opportunities of governmental expenditure are becoming particularly urgent. It is emphasized that a key factor in public sector’s performance is the public good, which ensures services of government institutions, and encompasses both quantitative and qualitative aspects. However, economic researches on the public sector’s performance efficiency focus on problems related to the determination of the public good as well as activate the possibility for its practical application. The US economist W.A. Niskanen mathematically grounded the bureau performance balance-shaping principles in the context of possibilities for evaluation of public administration, id est. the situation in which the institution’s performance can be evaluated as effective. In order to evaluate efficiency aspects of the public sector’s performance as well as their potential impact on the formation process of the state budget spending part, the authors of the research put forward the following objective – to perform mathematical calculations of bureau performance balance-shaping principles, grounded by the US economist W. A. Niskanen, and to assess the model’s potential opportunities for practical application. As a research novelty, the developed practical application software of Niskanen’s classical model of bureau performance is presented in MATLAB environment.