城市逐时用水量观测序列的混沌现象与最大可预测时间尺度。

Jing-qing Liu, Tu-qiao Zhang, Shen-kai Yu
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引用次数: 9

摘要

采用基于传统的Lyapunov指数最大Wolf算法的改进算法,研究了杭州市逐时用水量观测序列的混沌特征和最大可预测时间尺度。为了比较,我们分别计算了间隔1 h和间隔24 h的用水量序列的最大Lyapunov指数。结果表明:分时耗水系统存在明显的混沌特性;24小时间隔观测序列比逐时观测序列具有更长的最大可预测尺度。这些发现对于更好地预测城市小时用水量具有重要的实际应用价值。
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Chaotic phenomenon and the maximum predictable time scale of observation series of urban hourly water consumption.
The chaotic characteristics and maximum predictable time scale of the observation series of hourly water consumption in Hangzhou were investigated using the advanced algorithm presented here is based on the conventional Wolf’s algorithm for the largest Lyapunov exponent. For comparison, the largest Lyapunov exponents of water consumption series with one-hour and 24-hour intervals were calculated respectively. The results indicated that chaotic characteristics obviously exist in the hourly water consumption system; and that observation series with 24-hour interval have longer maximum predictable scale than hourly series. These findings could have significant practical application for better prediction of urban hourly water consumption.
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