Adaptive Data Processing Framework for Efficient Short-Term Traffic Flow Prediction

Accurate short-term traffic forecasting is a prerequisite for establishing intelligent transportation systems. In this paper, a new adaptive traffic flow sequence framework is processed. For any given dataset, the framework divides the original sequence into different time periods, generating an adaptive traffic flow sequence. Compared with the sequence using fixed aggregation intervals, adaptive traffic flow data is reduced by 33