Power load prediction method considering temperature fuzzification

The invention discloses a power load prediction method considering temperature fuzzification, and the method comprises the steps: firstly collecting historical load data, historical temperature dataand related date data of a power grid, processing the historical load data, historical temperature data and related date data into a 15-dimensional feature vector, and dividing the 15-dimensional feature vector into a training data set and a test data set in proportion; establishing a three-layer long-short-term memory neural network, and performing iterative training on the three-layer long-short-term memory neural network through the training data set to obtain a power load prediction model; and finally, inputting prediction day data in the test data set into the power load prediction modelto obtain a power load prediction value. According to the invention, the short-term load can be accurately predicted by considering the load timing characteristics; and meanwhile, a membership function is used for fuzzifying th