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NEURAL MODELING OF THE ELECTRIC POWER STOCK MARKET IN USAGE OF MATLAB AND SIMULINK TOOLS FOR THE DAY AHEAD MARKET DATA

100%
Ruciński D., Tchórzewski J.
Information Systems in Management
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2016
|
vol. 5
|
issue 2
215-226
EN
The work contains selected results of the modelling of neural Electric Power Ex-change (EPE) in Poland. For modelling EPE system, artificial neural network (ANN) was constructed. ANN was learned and tested using of the next day market data. Generated neural model was used for simulation tests and susceptibility tests. Suitable model was implemented in Simulink. As a result of simulation tests and susceptibility testing a lot of interesting research results were obtained.
2
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Predicting Future GDP Development by Means of Artificial Intelligence

88%
Jaromír V.
Littera Scripta
|
2016
|
issue 3
154-167
EN
GDP measures the monetary value of the total production of goods and services in a given country over a certain period of time. GDP establishes the economic performance of a country or region and is useful for comparing differences in the living standards of nations. In general, three methods exist for determining GDP, based on production, expenditure and income. In today's modern world, economists are looking for other appropriate and improved models for the management and prediction of all economic indicators. Artificial intelligence is among those methods that have gained in importance because of its very good predictive ability over conventional statistical and mathematical models. It consists of a time series, for example, but especially of artificial neural networks. This paper describes the known applications of artificial intelligence for the prediction of GDP and then applies neural networks to predict the GDP growth of Eurozone countries until the year 2025. The selected neural structures exhibit satisfactory numerical characteristics and are equivalent to expert evaluations of GDP development. They therefore appear to be a useful tool for predicting GDP.
3
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CAPABILITIES OF MATLAB AND SIMULINK RELATED TO MODELLING OF POLISH POWER EXCHANGE

75%
Tchórzewski J.
Information Systems in Management
|
2016
|
vol. 5
|
issue 3
424-435
EN
The paper presents selected results of research on modelling a system of the POLISH Power Exchange in the MATLAB and Simulink environment. Modelling capabilities of various toolboxes and Matlab language were presented. Special attention was paid to identification modelling using System Identification Toolbox, neural modelling using Neural Network Toolbox and simulation modelling using Simulink. Research experiments were preformed based on the Day Ahead Market quotations. The obtained models of th type in SIT, an artificial neural network (ANN) in NNT and a block diagram in Simulink were subjected to comparative and sensitivity tests. Final results were interpreted.
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