VMD-CNN-LSTM (unoptimized) and VMD-KOA-CNN-LSTM Comparison of the model prediction results with the actual power (Station site1).

VMD-CNN-LSTM (unoptimized) and VMD-KOA-CNN-LSTM Comparison of the model prediction results with the actual power (Station site1).

<p>VMD-CNN-LSTM (unoptimized) and VMD-KOA-CNN-LSTM Comparison of the model prediction results with the actual power (Station site1).</p>

Saved in:

Bibliographic Details
Main Author:	Jiangli Yu (4601986) (author)
Other Authors:	Gaoyi Liang (22311429) (author), Lei Wang (6656) (author), Huiyuan He (22311432) (author), Yuxin Liu (505575) (author), Qi Liu (33068) (author), Xinjie Cui (498116) (author), Hao Wang (39217) (author)
Published:	2025
Subjects:	Biotechnology Plant Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified mean absolute error decomposed modal components solid data foundation reduce data complexity photovoltaic power stations photovoltaic power generation term power prediction traditional prediction model lstm combined model kepler optimization algorithm kepler algorithm prediction accuracy data preprocessing power system power changes lstm leverages xlink "> three work subsequent predictions study focuses strongly proves stable operation significant optimization result correction reliable method proposed method innovatively introduce innovative idea grid connection great significance frequency characteristics fluctuating problems evaluation indicators entire process dynamic trends deeply integrated
Tags:	Add Tag No Tags, Be the first to tag this record!

Description
Summary:	<p>VMD-CNN-LSTM (unoptimized) and VMD-KOA-CNN-LSTM Comparison of the model prediction results with the actual power (Station site1).</p>

Cannot write session to /tmp/vufind_sessions/sess_5hdb253he3k141hsj6v7rdm3cc