Interval Forecasting of Financial Time Series by Accelerated Particle Swarm-Optimized Multi-Output Machine Learning System
By providing a range of values rather than a point estimate, accurate interval forecasting is critical to the success of investment decisions in exchange rate markets. This work proposes a sliding-window metaheuristic optimization for interval-valued time series forecasting using multi-output least...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
IEEE
2020-01-01
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Series: | IEEE Access |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/8955860/ |