Research on Artificial Intelligence Platform for Power Dispatching Based on Cloud Native Technology

Due to the complexity of the composition of surface features information in remote sensing images, the recognition and mapping effects are often difficult to meet the actual application needs. Therefore, the research on remote sensing image surface features recognition and vectorization mapping based on artificial intelligence is proposed. In the construction stage of remote sensing image feature map, based on the internal relationship between remote sensing data points, the feature map is used to reflect the local similarity characteristics of remote sensing data; Through the semi supervised mechanism of artificial intelligence algorithm - Markov random field model, the specific information of the ground object map is recognized. In the mapping stage, the constrained geometry algorithm is introduced, and the CGA rule file is used as a component to drive the 3D creation process. After the integration of basic terrain and 2D spatial data, the mapping is completed by aligning the footprint of the figure recognition object with the terrain network. In the test results, the OA corresponding to the recognition results of the design method has obvious advantages in stability and specific level compared with the control group, and mapping can effectively reflect the details of ground objects.