In phase space reconstruction of time sequences, the selection of embedding dimension is important.
嵌入维是时间序列相空间重构中的基本参数。
The minimum embedding dimension of reconstruction is confirmed by the false nearest neighbours method.
利用伪最邻近点法确定相空间重构的最小嵌入维数。
Based on local linear prediction model of chaotic time series, short-term load forecasting method on multi-embedding dimension is presented.
基于混沌时间序列的局域线性预测模型，提出了多嵌入维的短期负荷预测方法。
The relationship of embedding dimension and delay time is discussed and a new concept namely the generalized embedding Windows is put forward.
论述相空间重构中延迟时间与嵌入维数之间的关系，提出广义嵌入窗长的概念。
By phase space reconstruction, choosing the most suitable delay time and embedding dimension in order to embed time series which reflect the demanding into the phase space.
通过相空间重构技术，选取合适的延迟时间和嵌入维数，将反映市场需求的时间序列嵌入到相空间中。
Based on the idea of looking at the behavior of near neighbors under changes in the reconstruction dimension, a new method to determine the proper minimum embedding dimension is constructed.
本文基于“增大重构维以减少虚邻点”的思想，构造了一种求合适最小嵌入维的方法。
Based on the idea of looking at the behavior of near neighbors under changes in the reconstruction dimension, a new method to determine the proper minimum embedding dimension is constructed.
本文基于“增大重构维以减少虚邻点”的思想，构造了一种求合适最小嵌入维的方法。
应用推荐