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EN
To implement speed regulation algorithms of PMSM motor on real object the exact model encompassing imperfections of digital measurement and AC-DC-AC converter is required. The aim of the following paper is to present this kind of simulation model of the neural speed regulation system of PMSM motor in Matlab – Simulink. In the beginning the direct-quadrature transform and mathematical model of permanent magnet synchronous motor in dq coordinate system are shown. The paper shows speed measurement algorithm which ensure digital character of the output data. In the second section the neural speed controller trained on-line by backpropagation algorithm and the method for calculating gradient of error function are described. At the end of the paper simulation results validating proper behaviour of neural speed regulation system of PMSM motor are shown.
EN
Stock prediction with data mining techniques is one of the most important issues in finance. This field has attracted great scientific interest and has become a crucial research area to provide a more precise prediction process. This study proposes an integrated approach where Haar wavelet transform and Artificial Neural Network optimized by Directed Artificial Bee Colony algorithm are combined for the stock price prediction. The proposed approach was tested on the historical price data collected from Yahoo Finance with different companies. Furthermore, the prediction result was found satisfactorily enough as a guide for traders and investors in making qualitative decisions.
3
Content available remote Fuzzy neural networks with an application to medical diagnosis
EN
A hybrid learning procedure for fuzzy neural networks is presented. In the first stage the genetic algorithm performs global search and seeks a near-optimal initial point for the second stage which is based on the back-propagation algorithm. An application to medical diagnosis is described.
PL
W artykule przedstawiono hybrydową procedurę uczenia rozmytych sieci neuronowych. W pierwszym etapie uczenia algorytm genetyczny poszukuje rozwiązania bliskiego optimum, które stanowi punkt początkowy dla algorytmu wzorowanego na metodzie wstecznej propagacji błędów i wykorzystywanego w drugim etapie uczenia. W pracy opisano zastosowanie rozmytej sieci neuronowej do diagnostyki medycznej.
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