Bus Load Forecasting Based on K-means and Long Short-Term Memory Networks
Author:
Affiliation:
1. Dongguan Power Supply Bureau Guangdong Power Grid Co., Ltd,Dongguan,China
2. Guangdong Power Grid Co., Ltd,Power Dispatching Control Center,Guangzhou,China
3. China University of Geosciences,School of Automation,Wuhan,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10239547/10239550/10239628.pdf?arnumber=10239628
Reference13 articles.
1. A hybrid short-term load forecasting model based on variational mode decomposition and long short-term memory networks considering relevant factors with Bayesian optimization algorithm
2. Short-term microgrid load probability density forecasting method based on k-means-deep learning quantile regression
3. Short-term load forecasting using neural network with principal component analysis
4. Electricity load forecasting based on autocorrelation analysis
5. Short-Term Load Forecasting for Electric Bus Charging Stations Based on Fuzzy Clustering and Least Squares Support Vector Machine Optimized by Wolf Pack Algorithm
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