Because the learning vector quantization learning（LVQ） neural network is sensitive to initial weights and its competition layer is not fully utilized in GIS UHF partial discharge recognition process

a GIS UHF partial discharge recognition model is proposed by employing the mind evolutionary algorithm（MEA）to optimize LVQ neural network.This model uses K-cross validation to determine the optimal number of neurons in the LVQ network competition layer

then adopts MEA to find the optimal initial weights of the LVQ network

thus the optimal partial discharge recognition network model is constructed.Compared with the models with BP neural network

LVQ neural network

and K-cross validation LVQ neural network in GIS UHF partial discharge recognition accuracy

the MEA optimized LVQ neural network has the highest recognition accuracy.