Charging station quantity planning model based on neural network and electric load forecasting model

Abstract

The theory and design method of campus traffic planning is an important part of the overall campus planning. At present, the planning and design of university campus roads refer to the planning and design of urban roads to a great extent, but there are some differences between the urban traffic organization and that of university campus. The intelligent transportation system needs the traffic state prediction of the road network, but most of the current traffic state prediction methods are single-section prediction methods, which seldom consider the relationship between adjacent sections. Only the simple sum of traffic conditions of each section can not reflect the spatial distribution of road network sections. In this paper, through the analysis and research of road planning and design and road traffic organization of university campus, an intelligent planning model of university campus road based on support vector machine (SVM) algorithm is proposed. The experimental results show that the errors of this algorithm are small, and the accuracy rate is high, reaching 92.84%, which is about 18% higher than the traditional algorithm. Therefore, this method can build a good campus humanistic environment and natural environment, and effectively reduce the interference of motor vehicles on students.