基于注意机制和滚动更新的短期负荷预测双向长短时记忆方法数据集

基于注意机制和滚动更新的短期负荷预测双向长短时记忆方法数据集是“Bi-directional Long Short-term Memory Method based on Attention Mechanism and Rolling Update for Short-Term Load Forecasting”SCI论文关键数据集，数据内容为澳大利亚维多利亚州为案例的负荷预测数据，采集方案为参考文献和软件仿真，主要用于负荷预测研究。

The dataset corresponding to the Bi-directional Long Short-term Memory Method based on Attention Mechanism and Rolling Update for Short-Term Load Forecasting is a key dataset of the associated SCI paper. Taking Victoria, Australia as the research case, its data consists of load forecasting data. The data collection is carried out via literature collation and software simulation, and this dataset is primarily used for short-term load forecasting research.

搜集汇总

背景与挑战

背景概述

该数据集是用于短期负荷预测的关键数据，基于注意机制、滚动更新和双向长短时记忆方法构建。它以澳大利亚维多利亚州为案例，通过参考文献和软件仿真采集，主要服务于负荷预测相关研究。