Intelligent multimedia urban planning Construction based on spectral clustering algorithms of large data mining

摘要

This paper presents a spatio-temporal analysis method of intelligent urban road planning congestion based on spectral clustering algorithm of large data mining. Firstly, a time-space model of intelligent urban road planning congestion based on four-dimensional spatial temporal data of GIS is established, it uses the solution of additional virtual data to improve the sampling density of time dimension smart urban road planning congestion data. Secondly, the training planning data are clustered according to time in time and space so that the planning data with the same or similar time are in the same class. Then, each time class is clustered according to regional characteristics, and similar regions are clustered into the same block. Then it uses the Dobemoulli model to find the joint probability distribution between each block and time in the time class; finally, the joint probability distribution model is used to mine knowledge from unlabeled planning data, the effectiveness of the proposed method is verified by simulation experiments.