The invention discloses a
power grid construction subpackage management and control method based on
big data, and the method comprises the following steps: collecting the data of a
power grid construction site in real time, carrying out the preprocessing, and carrying out the storage through a distributed storage
system; generating a comprehensive evaluation report by using the
residual neural network and the graph convolutional network; adopting a
particle swarm optimization algorithm to carry out subpackage provider selection and task allocation; predicting the construction progress through a long short-
term memory network; performing
image analysis on the video
stream of the construction site by using a
residual neural network and a single-time multi-frame detection
algorithm; a
Bayesian network and a multi-layer
perceptron are used to predict construction risks, an isolated forest
algorithm is used to carry out abnormal value detection on data, and a risk early warning report is generated and notified to related personnel. According to the invention,
big data,
deep learning and
reinforcement learning technologies are fully combined, the
power grid construction subpackage management and control method based on
big data is described in detail, and the method has the advantages of high construction efficiency, accurate risk prediction and resource optimization.