Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models

Shunsuke Tsuzuki; Yu Nishiyama

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arXiv · 1811.06210

Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models

Shunsuke Tsuzuki·Yu Nishiyama

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Abstract

In machine learning, a nonparametric forecasting algorithm for time series data has been proposed, called the kernel spectral hidden Markov model (KSHMM). In this paper, we propose a technique for short-term wind-speed prediction based on KSHMM. We numerically compared the performance of our KSHMM-based forecasting technique to other techniques with machine learning, using wind-speed data offered by the National Renewable Energy Laboratory. Our results demonstrate that, compared to these methods, the proposed technique offers comparable or better performance.

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BibTeX RIS

Shunsuke Tsuzuki, Yu Nishiyama. 2018-11-15. Short-Term Wind-Speed Forecasting Using Kernel Spectral Hidden Markov Models. https://arxiv.org/abs/1811.06210

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