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A Novel Ensemble Neuro-Fuzzy Model for Financial Time Series Forecasting

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Department of Artificial Intelligence, Faculty of Computer Science, Kharkiv National University of Radio Electronics, 61166 Kharkiv, Ukraine
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Department of Informatics and Computer Engineering, Faculty of Economic Informatics, Simon Kuznets Kharkiv National University of Economics, 61166 Kharkiv, Ukraine
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Information Technology Department, IT Step University, 79019 Lviv, Ukraine
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Control Systems Research Laboratory, Kharkiv National University of Radio Electronics, 61166 Kharkiv, Ukraine
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Author to whom correspondence should be addressed.
Data 2019, 4(3), 126; https://doi.org/10.3390/data4030126
Received: 30 June 2019 / Revised: 15 August 2019 / Accepted: 20 August 2019 / Published: 23 August 2019
(This article belongs to the Special Issue Data Analysis for Financial Markets)
Neuro-fuzzy models have a proven record of successful application in finance. Forecasting future values is a crucial element of successful decision making in trading. In this paper, a novel ensemble neuro-fuzzy model is proposed to overcome limitations and improve the previously successfully applied a five-layer multidimensional Gaussian neuro-fuzzy model and its learning. The proposed solution allows skipping the error-prone hyperparameters selection process and shows better accuracy results in real life financial data. View Full-Text
Keywords: time series; neuro-fuzzy; ensemble; model averaging; Gaussian; prediction; stochastic gradient descent time series; neuro-fuzzy; ensemble; model averaging; Gaussian; prediction; stochastic gradient descent
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Vlasenko, A.; Vlasenko, N.; Vynokurova, O.; Bodyanskiy, Y.; Peleshko, D. A Novel Ensemble Neuro-Fuzzy Model for Financial Time Series Forecasting. Data 2019, 4, 126.

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