Exploring the effectiveness of a multilayer neural network model for gold price prediction

• Autorzy: Gbadamosi Saheed Lekan , Nwulu Nnamdi I. , Akinola Solomon Oluwole

Identyfikatory

DOI

10.15199/48.2024.03.28

Warianty tytułu

PL

Badanie efektywności wielowarstwowego modelu sieci neuronowej do przewidywania ceny złota

• Języki publikacji: EN

Abstrakty

EN

Effective gold price forecasting model is an essential tool for price discovery and benchmarking market changes for mining project across the world. This study presents a model for effective prediction of gold price variation across the world. An experimental analysis was conducted for forecasting monthly US market gold prices from December 1978 to March 2023 using the Autoregressive Integrated Moving Average (ARIMA) model and Multilayer perceptron (MLP) regression model. Optimized hyperparameter search determined the lowest Mean Squared error (MSE) and Mean Absolute (MAE) results with ARIMA (2, 1, 1) and MLP best parameters. The proposed multilayer perceptron (MLP) model demonstrates an improvement in the effective prediction obtained from the experimental analysis

PL

Efektywny model prognozowania cen złota jest niezbędnym narzędziem do odkrywania cen i porównywania zmian rynkowych dla projektów wydobywczych na całym świecie. W badaniu przedstawiono model skutecznego przewidywania zmian cen złota na świecie. Przeprowadzono analizę eksperymentalną w celu prognozowania miesięcznych cen złota na rynku amerykańskim od grudnia 1978 r. do marca 2023 r., stosując model autoregresyjnej zintegrowanej średniej ruchomej (ARIMA) i model regresji perceptronu wielowarstwowego (MLP). Zoptymalizowane wyszukiwanie hiperparametrów pozwoliło uzyskać najniższe wyniki błędu średniego kwadratowego (MSE) i średniego bezwzględnego (MAE) z najlepszymi parametrami ARIMA (2, 1, 1) i MLP. Zaproponowany model perceptronu wielowarstwowego (MLP) wykazuje poprawę efektywnej predykcji uzyskanej na podstawie analizy eksperymentalnej.

Słowa kluczowe

EN

gold price; prediction; multilayer neural network

PL

cena złota; prognoza; wielowarstwowa sieć neuronowa

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2024
• Tom: R. 100, nr 3
• Strony: 157--161
• Opis fizyczny: Bibliogr. 39 poz., rys., tab.

Twórcy

autor

Gbadamosi Saheed Lekan

• Center for Cyber Physical Food, Energy and Water Systems, University of Johannesburg, Auckland Park 2006, South Africa
• Department of Electrical, Electronic and Computer Engineering, Afe Babalola University Ado-Ekiti, Nigeria

• https://orcid.org/0000-0001-7398-813

autor

Nwulu Nnamdi I.

• Center for Cyber Physical Food, Energy and Water Systems, University of Johannesburg, Auckland Park 2006, South Africa

autor

Akinola Solomon Oluwole

• Department of Electrical, Electronic and Computer Engineering, Afe Babalola University Ado-Ekiti, Nigeria

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).