文章基本信息

标题：A hybridized ELM-Jaya forecasting model for currency exchange prediction
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作者：Smruti Rekha Das ; Debahuti Mishra ; Minakhi Rout 等
期刊名称：Journal of King Saud University @?C Computer and Information Sciences
印刷版ISSN：1319-1578
出版年度：2020
卷号：32
期号：3
页码：345-366
DOI：10.1016/j.jksuci.2017.09.006
出版社：Elsevier
摘要：This paper establishes a hybridized intelligent machine learning based currency exchange forecasting model using Extreme Learning Machines (ELMs) and the Jaya optimization technique. This model can very well forecast the exchange price of USD (US Dollar) to INR (Indian Rupee) and USD to EURO based on statistical measures, technical indicators and combination of both measures over a time frame varying from 1 day to 1 month ahead. The proposed ELM-Jaya model has been compared with existing optimized Neural Network and Functional Link Artificial Neural Network based predictive models. Finally, the model has been validated using various performance measures such as; MAPE, Theil's U, ARV and MAE. The comparison of different features demonstrates that the technical indicators outperform both the statistical measures and a combination of statistical measures and technical indicators in ELM-Jaya forecasting model.
关键词：Currency exchange prediction ; Extreme Learning Machine (ELM) ; Jaya ; Neural Network (NN) ; Functional Link Artificial Neural Network (FLANN)