基于小波分解的智能交通系统数据集成方法

Optimized aggregation level for ITS data based on wavelet decomposition

对于智能交通系统 (ITS)的数据集成 ,数字信号处理技术中的小波变换方法能够克服传统的基于数理统计方法的集成技术的种种缺陷 ,并提供最佳集成度。该文基于小波分解的方法 ,通过对 ITS数据进行分层、相似性分析得出了数据的最佳集成度 ,完成了对数据的集成。通过该方法集成后的数据不仅包含足够的有用信息 。

Wavelet decomposition is a new technique in intelligent transportation system (ITS) data aggregation that can overcome the shortcomings of conventional techniques based on statistical comparison to determine the aggregation level. Then, decomposition and similarity analysis of the ITS data were used to optimize the aggregation level. The desired information is retained in the aggregated data derived from the wavelet analysis while the errors and noises are filtered.