A Dynamic Model for Predicting Indoor Temperatures based on CBLSTM and Auto Encoder Approach-Reference-Cited by-同舟云学术

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A Dynamic Model for Predicting Indoor Temperatures based on CBLSTM and Auto Encoder Approach

Published:2023-12-11 Issue: Volume:14 Page:1147-1152
ISSN:
Container-title:2023 2nd International Conference on Automation, Computing and Renewable Systems (ICACRS)
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Author:

Karri Murali¹,Fulzele Prasenjit Yashwant²,Ansari Mohammed Saleh Al³,Devendraiah K. M.⁴,Umamaheswari B.⁵,Singh Dharmendra⁶

Affiliation:

1. Geetanjali College of Engineering and Technology,Department of EEE,Hyderabad,India

2. Bharati Vidyapeeth College of Engineering,Department of Mechanical Engineering,Navi Mumbai,India

3. University of Bahrain,Department of Chemical Engineering,Bahrain

4. V. V. Sangha’s Independent P U College,Ballari,India

5. Prince Shri Venkateshwara Padmavathy Engineering College,Department of CSE,Chennai,India

6. School of Management Sciences,Lucknow,India

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10404046/10404076/10404338.pdf?arnumber=10404338

Reference24 articles.

1. A review of thermal comfort models and indicators for indoor environments

2. Smart Building: Use of the Artificial Neural Network Approach for Indoor Temperature Forecasting

3. Improving prediction performance for indoor temperature in public buildings based on a novel deep learning method

4. LSTM-based indoor air temperature prediction framework for HVAC systems in smart buildings

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