建立一种基于结构时间序列模型的新的时间序列季节调整方法。
In the paper, we construct a new seasonal adjustment method of time series on the basis of the structural time series model.
把最终的季节时间序列模型转化为状态空间形式，通过卡尔曼滤波实时调整状态向量，实现电梯交通流的在线预测。
It transforms the finial SARIMA model to state space model, adjusts the state vector using Kalman filter, and realizes the on-line forecast.
把最终的季节时间序列模型转化为状态空间形式，通过卡尔曼滤波实时调整状态向量，实现电梯交通流的在线预测。
It transforms the finial SARIMA model to state space model, adjusts the state vector using Kalman filter, and realizes the on-line forecast.
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