基于复杂性测度的泊位占有率序列动力学分析

Dynamicsanalysis of parking space occupancy series based on complexity measurement

为了定量分析停车场泊位占有率时间序列的动力学特性,对序列进行复杂性测度分析.利用主分量分析方法分析序列的主分量谱图,判断序列的混沌特性;计算序列的联合熵分析序列的非线性特性,计算序列的C0复杂度分析序列中的非规则成分,综合两种复杂性测度方法对序列的动力学特性进行分析.对比分析几种典型序列和泊位占有率序列发现,泊位占有率时间序列的线性特征更明显,序列中所含的规则成分较多,是一种"拟周期"序列.利用C0复杂度的思想剔除不规则成分,对序列进行长时预测,结果表明,剔除不规则成分后的预测精度提高了26%~56%,长时预测效果提高显著.

The analysis of the sequence was conducted based on complexity measurement in order to quantitatively analyze the dynamic characteristics of parking space occupancy time series.The principal component analysis was used to analyze the principal component spectrum of the sequence.The nonlinear characteristic of the sequence was calculated by the joint entropy of the sequence.Irregular components of the sequence were analyzed by calculating the C0 complexity of the sequence.The analysis of comparing with several typical time series shows that the time series of parking space occupancy is a kind of sequence which situated between linearity and nonlinearity,and its linear characteristic is more significant.The sequence contains more regular components,which can be seen as a‘quasi-periodic’sequence,but the extremely irregular components in the original series can increase the prediction error in long-term prediction.Long-term prediction of parking space series was conducted by using the idea of C0 complexity.Results show that the prediction accuracy increases by 26%to 56%after eliminating irregular components in the original series,which shows better performance.