1) time series forecast with equal step length
等步长时序预测
2) step-ahead prediction
步长预测
3) predictive time length
预测步长
1.
Furthermore,an iterative learning for predictive time length is proposed which is tuned by iterative learning based on system errors of previous control periods online.
同时,将迭代学习思想引入到预测步长的在线调整,提出了预测步长的迭代学习方法。
4) Multi-steps time series prediction
多步时间序列预测
5) time series prediction
时序预测
1.
In order to reflect the change in deformation of surrounding rocks in soft rock bolt-grouting roadway along with time,we have built the time series prediction model of the deformation of surrounding rock in soft rock bolt-grouting roadway based on the RBF neural network and the data of the deformation observed from the locale.
为反映软岩锚注巷道围岩的变形在时间上的变化规律,利用径向基函数RBF神经网络强大的非线性映射能力,通过已经观测到的巷道围岩变形数据,建立软岩锚注巷道围岩变形量的时序预测模型。
6) Time series forecasting
时序预测
1.
Time series forecasting models of food-grain consumption per capita in China were scanned and selected by using SPSS, and were built based on the correlative relationship between quantity of consumption and time.
利用粮食消费量与时间之间的相关关系, 采用SPSS程序包进行筛选, 建立我国人均食用粮食消费的时序预测模型。
2.
Time series forecasting models of total food-grain consumption in China were selected by using SPSS, and were built based on the correlative relationship between quantity of consumption and time.
利用粮食消费量与时间之间的相关关系 ,采用SPSS程序包进行筛选 ,建立我国食用粮食消费总量的时序预测模型。
补充资料：发育进度预测法(见发生期预测)
发育进度预测法(见发生期预测)
发育进度预测法见发生期预测。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条