Abstract: his paper proposes a distribution network electrical topology identification algorithm based on a multi-channel adaptive weighted neural network. The algorithm builds a multi-channel 1DCNN (one-dimensional convolutional neural network) model, and uses four types of data: voltage, current, power and power factor, to make the datasets. Feature extraction has been realized through two CNN layers stacked; Meanwhile, an adaptive weighted feature fusion is proposed, it can learn the importance of each channel's feature through neural network adaptively. Datasets collect real consumption data, and multiple sets of experiments are conducted with the number of channels, data types, data dimensions and other parameters. Results show that the proposed algorithm can integrate the advantages of multiple data features, the accuracy of electrical topology identification can reach 99.772%.