摘要
为了提高短期电力负荷预测的精准度,建立了一种将麻雀搜索算法、卷积神经网络算法和长短期记忆网络算法相结合的短期电力负荷预测模型,旨在更有效地处理短期电力负荷预测问题。
In order to improve the accuracy of short-term power load forecasting,a short-term power load forecasting model combining the sparrow search algorithm,the convolutional neural network algorithm and the long and short-term memory network algorithm is established,aiming to deal with short-term power load forecasting problems more effectively.
作者
赵艺然
王宇驰
原令泽
Zhao Yiran;Wang Yuchi;Yuan Lingze(School of Electrical and Control Engineering,Liaoning Technical University,Huludao Liaoning 125105,China)
出处
《现代工业经济和信息化》
2024年第8期169-170,共2页
Modern Industrial Economy and Informationization
关键词
麻雀搜索算法
卷积神经网络算法
长短期记忆网络
电力负荷预测
sparrow search algorithm
convolutional neural network algorithm
long and short-term memory network
power load forecasting
