Framework diagram of the proposed model.

<div><p>Accurate prediction of chiller energy consumption is crucial for reducing building energy consumption. In this study, an innovative dual-branch network architecture DNTB (A Dual-Branch Network Model Based on Transformer and Bi-LSTM for Energy Consumption Prediction in Building Ch...

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Bibliographic Details
Main Author:	Andong Chen (22367103) (author)
Other Authors:	Mingtao Wu (21837870) (author), Cheng Chen (136164) (author), Chen Chen (6544) (author), Yong Huang (15745) (author), Xiaoyi Lv (8671755) (author)
Published:	2025
Subjects:	Evolutionary Biology Ecology Science Policy Biological Sciences not elsewhere classified Information Systems not elsewhere classified mean square error mean absolute error experimental results indicate energy consumption prediction current prediction models chiller energy consumption term dependency modeling building chiller systems term prediction results dntb performs excellently term sequence information chiller temperature temporal information building load prediction model term tasks robust framework research goal noise sensitivity global dependencies generalization ability dntb enriches dew point data noise complementary characteristics chilled water better capture basic principle
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Framework diagram of the proposed model.

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