Load Forecasting for the Laser Metal Processing Industry Using VMD and Hybrid Deep Learning Models

F Aksan, V Suresh, P Janik, T Sikorski - Energies, 2023 - mdpi.com
Electric load forecasting is crucial for the metallurgy industry because it enables effective
resource allocation, production scheduling, and optimized energy management. To achieve …

[PDF][PDF] Grid search of multilayer perceptron based on the walk-forward validation methodology

TT Ngoc, LV Dai, DT Phuc - Int. J. Electr. Comput. Eng. IJECE, 2021 - academia.edu
Multilayer perceptron neural network is one of the widely used method for load forecasting.
There are hyperparameters which can be used to determine the network structure and used …

An effective deep learning neural network model for short‐term load forecasting

N Li, L Wang, X Li, Q Zhu - Concurrency and Computation …, 2020 - Wiley Online Library
Energy load forecasting plays an important role in the smart grid, which can affect the
promoting energy production and consumption decision‐making processes. In this paper …

A deep learning short-term load forecasting method for extreme scenarios

W Ling, Y Sun, Q Li, J Lin, J Hu… - Eighth International …, 2023 - spiedigitallibrary.org
Short-term load forecasting is a crucial for improving the level of power grid dispatching and
operation. In recent years, extreme weather occurs frequently, and deep learning is a …

[引用][C] 基于TPE 优化集成学习的短期负荷预测方法(网络首发)

罗敏, 杨劲锋, 俞蕙, 赖雨辰, 郭杨运, 周尚礼, 向睿… - 上海交通大学学报