The application discloses a kind of
machine learning training topology generator and the method for generating topological
discriminator model, comprising the following steps: with matrix pair form characterizing real topological data, and pre-
processing;Topology generator is constructed, and topological pseudo-matrix pair data is generated;Topological
discriminator is constructed to identify the source of topological data;The topological generator and the topological
discriminator are based on the adversarial training of
generative adversarial network;Low-
voltage area topological matrix pair data is generated, and is converted into visual
topological graph.The application realizes the
coevolution of topological generator and topological discriminator by constructing topological generator and topological discriminator and through the adversarial training of both, and then enables topological generator to automatically generate a large number of topological data in accordance with real
station area statistical distribution and
engineering rationality from simple input, with the technical effects of high generation quality, high
automation efficiency, guaranteeing physical rationality, solving data scarcity problem and strong flexibility and adaptability.