Development and application of an evolutionary deep learning framework of LSTM based on improved grasshopper optimization algorithm for short-term load forecasting

Author:

Hu Haowen,Xia Xin,Luo Yuanlin,Zhang Chu,Nazir Muhammad Shahzad,Peng Tian

Publisher

Elsevier BV

Subject

Mechanics of Materials,Safety, Risk, Reliability and Quality,Building and Construction,Architecture,Civil and Structural Engineering

Reference47 articles.

1. Short-term building electrical load forecasting using adaptive neuro-fuzzy inference system (ANFIS);Ghenai;J. Build. Eng.,2022

2. An Efficient CNN and KNN Data Analytics for Electricity Load Forecasting in the Smart Grid;Aimal,2019

3. Sequence-to-sequence neural networks for short-term electrical load forecasting in commercial office buildings;Skomski;Energy Build.,2020

4. Short-term electric load prediction using transfer learning with interval estimate adjustment;Jin;Energy Build.,2022

5. Dual-stage attention-based long-short-term memory neural networks for energy demand prediction;Peng;Energy Build.,2021

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