Decision system for stock data forecasting based on Hopfield artificial neural network

• Autorzy: Paluch M. , Jackowska-Strumiłło L.

Identyfikatory

DOI

10.5604/20830157.1201313

Warianty tytułu

PL

System decyzyjny do przewidywania cen akcji oparty na sztucznej sieci neuronowej Hopfielda

• Języki publikacji: EN

Abstrakty

EN

The paper describes a new method using Hopfield artificial neural network combined with technical analysis fractal analysis and feed-forward artificial neural networks for predicting share prices for a next day on a Stock Exchange. The developed method and networks are implemented in an Expert System, which is proposed as a valuable comprehensive, analytical tool. A new algorithm for artificial neural networks training and testing is also presented. It automatically chooses the best network structure, and the most important input parameters

PL

Artykuł opisuje nową metodę zastosowania sztucznej sieci neuronowej Hopfielda połączonej z analizą techniczną, fraktalną oraz jednokierunkowymi sztucznymi sieciami neuronowymi do przewidywania przyszłych cen akcji na Giełdzie Papierów Wartościowych. Opisane nowe metody zostały zaimplementowane w systemie ekspertowym, który jest polecany jako kompleksowe narzędzie do badania aktualnych i przyszłych zachowań rynku. Zaprezentowany został również algorytm nauki testowania sztucznych sieci neuronowych, który na końcu wybiera najlepszą z nich.

Słowa kluczowe

EN

hybrid intelligent system; Hopfield artificial neural network

PL

hybrydowy inteligentny system; sztuczna sieć neuronowa Hopfielda

• Wydawca: Wydawnictwo Politechniki Lubelskiej
• Czasopismo: Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
• Rocznik: 2016
• Tom: nr 2
• Strony: 28--33
• Opis fizyczny: Bibliogr. 28 poz., rys., tab.

Twórcy

autor

Paluch M.

• Lodz University of Technology, Institute of Applied Computer Science

autor

Jackowska-Strumiłło L.

• Lodz University of Technology, Institute of Applied Computer Science

Bibliografia

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Uwagi

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.