帮我降重一段话Abstract In this paper a short-term power network load forecasting algorithm based on evolutionary neural network is proposed In this paper an improved artificial bee colony algorithm is combin

This paper proposes a short-term power network load forecasting algorithm based on evolutionary neural network. An improved artificial bee colony algorithm is combined with BP neural network to generate an evolutionary neural network, and the bias and weight of the network are optimized by using the algorithm. The proposed algorithm takes historical load data of thermal power as input and uses evolutionary neural network to train the forecasting model to predict future power grid load. The experimental results show that the proposed method has good forecasting accuracy and practicability, with smaller prediction error and more accurate and reliable results compared to traditional methods.