Shore Power System Load Forecasting Model Based on QPSO-LSTM Network
Author:
Affiliation:
1. Shanghai Maritime University,China
2. Taiyuan University of Technology,China
3. Shanghai Zhenhua Heavy Industries Co., Ltd,China
4. CCCC Western Investment Co., Ltd,China
Funder
National Natural Science Foundation of China
China Southern Power Grid
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10567049/10567050/10567488.pdf?arnumber=10567488
Reference13 articles.
1. Green Port Strategies in China
2. Comparison and Analysis of the Current Situation of Port Shore Power Construction and Operation
3. Tackling ship pollution from the shore
4. Radial Basis Function Neural Networks-Based Short Term Electric Power Load Forecasting for Super High Voltage Power Grid[J];Ali;Journal of Engineering Science and Technology,2022
5. An Effective Short-Term Electrical Load Forecasting Model: A Constructive Neural Network Approach
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