Multi-dimensional attribute coupling full-life-cycle building energy consumption characterization and prediction updating method

The invention provides a multi-dimensional attribute coupling full-life-cycle building energy consumption characterization and prediction updating method, and relates to the technical field of data processing, and the method comprises the steps: obtaining multi-dimensional attributes of a target building in a full life cycle, the multi-dimensional attributes comprise multiple of geometric feature attributes, environment feature attributes, functional feature attributes and life cycle feature attributes; analyzing and processing the mapping association relationship between the building energy consumption and the multi-dimensional attributes based on a deep learning neural network, constructing a neural network with multiple neurons, and establishing a connection relationship between the neurons; performing training processing on gradient parameters of the neural network based on the pre-training data of the different life cycles to obtain gradient parameters corresponding to each neuron in the different life c