Forecasting currency exchange rate time series with fireworks algorithm-based higher order neural network, with special attention to training data enrichment

• Autorzy: Sahu Kishore Kumar , Nayak Sarat Chandra , Behera Himansu Sekhar

Identyfikatory

DOI

10.7494/csci.2020.21.4.3474

• Języki publikacji: EN

Abstrakty

EN

Exchange rates are highly fluctuating by nature; thus, they are difficult to forecast. Artificial neural networks (ANNs) have proven to be better than statistical methods. Inadequate training data may lead the model to reach sub-optimal solutions, resulting in poor accuracy (as ANN-based forecasts are data-driven). To enhance forecasting accuracy, we suggests a method of enriching training datasets through exploring and incorporating virtual data points (VDPs) by an evolutionary method called the fireworks algorithm-trained functional link artificial neural network (FWA-FLN). The model maintains a correlation between current and past data, especially at the oscillation point on the time series. The exploration of a VDP and forecast of the succeeding term go consecutively by FWA-FLN. Real exchange rate time series are used to train and validate the proposed model. The efficiency of the proposed technique is related to other similarly trained models and produces far better prediction accuracy.

Słowa kluczowe

EN

exchange rate; virtual data point; interpolation; artificial neural network; fireworks algorithm; functional link neural network

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Science
• Rocznik: 2020
• Tom: T. 21 (4)
• Strony: 463--488
• Opis fizyczny: Bibliogr. 48 poz., rys., tab.

Twórcy

autor

Sahu Kishore Kumar

• Veer Surendra Sai University of Technology, Department of Information Technology, Burla, Sambalpur, India

autor

Nayak Sarat Chandra

• CMR College of Engineering & Technology, Department of Computer Science and Engineering, Hyderabad – 501401, India

autor

Behera Himansu Sekhar

• Veer Surendra Sai University of Technology, Department of Information Technology, Burla, Sambalpur, India

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