Research on Short-Term Air Conditioning Cooling Load Forecasting Based on Bidirectional LSTM
Author:
Affiliation:
1. Hangzhou Power Supply Company, State Grid Zhejiang Electric Power Co., Ltd.,Hangzhou,China
2. HDU-ITMO Joint Institute, Hangzhou Dianzi University,Hangzhou,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9858895/9858938/09858975.pdf?arnumber=9858975
Reference8 articles.
1. Research on Forecast of Daily Electricity Consumption of Household Air Conditioning Based on Improved Long-short Memory Network
2. Short-term air conditioning cooling load prediction based on long short-term memory network [J];ziwei;HV&AC,2022
3. A bi-directional missing data imputation scheme based on LSTM and transfer learning for building energy data
4. Multi-Step Ahead Wind Power Generation Prediction Based on Hybrid Machine Learning Techniques
5. Research progress on air-conditioning load forecasting of public buildings in my country based on big data [J];xianyong;Anhui Architecture,2019
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2. Investigating Efficacy of RNN and its Variants for AQI Forecasting;2023 International Conference on Advances in Computation, Communication and Information Technology (ICAICCIT);2023-11-23
3. Air Conditioning Load Forecast Based on LSTM Combining Improved Particle Swarm Algorithm and Attention Mechanism;2023 China Automation Congress (CAC);2023-11-17
4. HVAC Load Forecasting Based on the CEEMDAN-Conv1D-BiLSTM-AM Model;Mathematics;2023-11-13
5. Forecasting Short-Term Indoor Radon: A Machine Learning Approach Using LSTM Networks;2023 18th Iberian Conference on Information Systems and Technologies (CISTI);2023-06-20
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