Energy Consumption Prediction and Diagnosis of Heating Ventilation and Air Conditioning System Based on Bidirectional LSTM Method-Reference-Cited by-同舟云学术

Energy Consumption Prediction and Diagnosis of Heating Ventilation and Air Conditioning System Based on Bidirectional LSTM Method

Published:2022-07 Issue: Volume: Page:
ISSN:
Container-title:2022 International Conference on Computer Engineering and Artificial Intelligence (ICCEAI)
language:
Short-container-title:

Author:

Cong YiLin¹,Hou LiTong¹,Wu YiCheng¹,Ma YongZhi¹

Affiliation:

1. Qingdao University, College of mechanical and electrical engineering,Qingdao,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9853204/9853314/09853346.pdf?arnumber=9853346

Reference11 articles.

1. A long short-term memory artificial neural network to predict daily HVAC consumption in buildings

2. A novel deep reinforcement learning based methodology for short-term HVAC system energy consumption prediction

3. A Deep Learning Neural Network for the Residential Energy Consumption Prediction

4. A simplified prediction model for energy use of air conditioner in residential buildings based on monitoring data from the cloud platform

5. An attention-basedCNN-LST M-BiLSTMmodel for short-term electric load forecasting in integrated energy system;wu;International Transactions on Electrical Energy Systems,2021

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