데이터셋 상세
미국
Long-term prediction of nonlinear time series
This paper is about applying recurrent least squares support vector machines (LS-SVM) on three ESTSP08 competition datasets. Least squares support vector machines are used as nonlinear models in order to avoid local minima problems. Then prediction task is re-formulated as function approximation task. Recurrent LS-SVM uses nonlinear autoregressive exogenous (NARX) model to build nonlinear regressor, by estimating in each iteration the next output value, given the past output and input measurements.
데이터 정보
- 데이터 포털
- 미국
- META URL
- https://catalog.data.gov/dataset/long-term-prediction-of-nonlinear-time-series
- 라이선스
- notspecified
- 비용
- 제공기관
- National Aeronautics and Space Administration
- 관리부서
- 데이터
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