Abstract:In order to overcome the difficulty that after the single-line diagram of the distribution network is automatically drawn, a tremendous amount of manual adjustment is required to satisfy the practical standards. This article focused on an automatic mapping system platform of a distribution network in Guizhou, introduced via machine learning technology of The Big Data Spark framework to single-line graph layout algorithm, with emphasis on its application usage. First, it introduced the technical architecture of the automatic mapping system and elaborated the application environment of machine learning technology, proposed to build a decision tree machine learning model based on iterative dichotomiser 3 generation（ID3）algorithm, using the distribution network data as training samples, describing the construction process of the decision tree model. Further, the sample data adjusted by graphics is used as the training set, to train the child devices relative to the parent device in the differential layout algorithm. Finally, the single-line diagram data examples of the distribution network are used to verify the machine learning model and the difference layout algorithm. The results showed that after using the algorithm, the generated single-line diagram is horizontal and vertical, the station building is layered and balanced, thus the layout is fine and legit. This proves the effectiveness of the application of big data and machine learning techniques in the automatic layout of single-line diagrams.