Study On Prediction Model Of Electric Power Communication Flow Based On Wisdom City

Smart city is a new mode of city development, to promote social harmony and healthy development, to realize the information management more efficient, more open, more beautiful environment, the harmony of society, a better life. Electric power communication network with power production, construction and management came into being, the accumulation of covering a wide range of electric power information and communication infrastructure, urban construction and development needs the support of communication resource of wisdom. Electric power communication network traffic prediction is an important basis for the safety of power system dispatching, economic operation, its precision directly affects the operation of the power system reliability, economy and the quality of power supply. Therefore, seeking an appropriate forecasting method to maximize the improvement of prediction precision has important application value.First of all, this paper expounds on the wisdom of city and smart grid status, briefly summarizes the current research situation and to forecast the power communication traffic, analyzes the flow characteristics, and the predicted influence factors were collated, summarized the common means of power communication traffic prediction, and the analysis of their advantages and disadvantages are compared; introduction of the principle of least squares the algorithm of support vector machine, introduces the particle swarm optimization algorithm, the use of PSO for the two important parameters in LSSVM are optimized for the optimization process, prone to the standard particle swarm algorithm of the premature convergence problem, introducing the concept of average distance; based on historical traffic data of a certain area, analysis the influence factor, regularity summary of flow change, and the model input data pre-processing; analysis of current situation of electric power communication network are selected to establish the prediction model of the city, traffic, and select test set error as the judgment basis, in order to realize the optimization choice of model parameters, so the prediction precision is improved. The practical examples show that the prediction accuracy of this prediction method has higher, can be used to predict the flow of power communication network prediction.