城市兴趣点演化规律的可预测性分析

A PLCPA model was established to describe the predictability of urban point-of-interest evolution. Based on the change of urban interest points in continuous time window, a definition of the life cycle length and life cycle status was given and the predictability of point-of-interest evolution was analyzed. Fano's inequality was combined with the life cycle length and status of urban point-of-interest to quantify the predictability of the evolution of urban point-of-interest. And the predictability calculation of life cycle length and status of urban point-of-interest was given based on the information uncertainty measure in the information theory. The predictability of different categories of point-of-interest with different levels of granularity was calculated according to the urban point-of-interest data of seven cities. Results show that the life cycle of urban interest points is predictable; the predictabilities of different categories of point-of-interest are quite different; the predictability of the points-of-interest in the decaying status is higher than that of the stable status and the booming status.