A novel trilinear deep residual network with self-adaptive Dropout method for short-term load forecasting

Qian Chen, Wenyu Zhang, Kun Zhu, Di Zhou, Hua Dai, Quanquan Wu

Abstract: Highlights•A novel deep residual network with self-adaptive Dropout method is proposed.•A trilinear deep residual network solves vanishing gradient and exploding gradient.•The self-adaptive Dropout method sets the neuron drop ratio automatically.•The neural network ensemble method enhances the forecasting accuracy.•The performance of the proposed model is superior to other comparative models.