A Hybrid Short-Term Load Forecasting Model Based on Improved Fuzzy C-Means Clustering, Random Forest and Deep Neural Networks

A Hybrid Short-Term Load Forecasting Model Based on Improved Fuzzy C-Means Clustering, Random Forest and Deep Neural Networks

Short-term load forecasting (STLF) plays an important role in the secure and reliable operation of the electric power system. Grouping similar load profiles by a clustering algorithm is a common method to reduce the uncertainty of electric consumption data. However, due to the uneven distribution of...

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Bibliographic Details
Main Authors: Fu Liu, Tian Dong, Tao Hou, Yun Liu
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Clustering
fuzzy c-mean algorithm
load forecasting
random forest
deep neural network
Online Access:https://ieeexplore.ieee.org/document/9366756/

Internet

https://ieeexplore.ieee.org/document/9366756/

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