Deep Learning Method to Analyze the Bi-LSTM Model for Energy Consumption Forecasting in Smart Cities-Reference-Cited by-同舟云学术

Deep Learning Method to Analyze the Bi-LSTM Model for Energy Consumption Forecasting in Smart Cities

Published:2023-11-15 Issue: Volume: Page:
ISSN:
Container-title:2023 International Conference on Sustainable Communication Networks and Application (ICSCNA)
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Author:

Balasubramaniyan S.¹,Kumar P.K.²,Vaigundamoorthi M.³,Rahuman A. Kaleel⁴,Solaimalai Gautam⁵,Sathish T.⁶,Vidhya R.G.⁷

Affiliation:

1. Mailam Engineering College,Department of Electrical and Electronics Engineering,Mailam

2. Sri Sairam Engineering College,Department of Physical Education,Chennai

3. Karpagam Academy of Higher Education,Department of Electrical and Electronics Engineering,Coimbatore

4. PSNA College Of Engineering And Technology,Department of Electronics and Communication Engineering,Dindigul

5. University of Austin Georgie tech,Department of Artificial Intelligence and Machine Learning,30332

6. Saveetha school of Engineering, SIMATS,Department of Mechanical Engineering,Chennai

7. HKBK College of Engineering,Department of ECE

Publisher

IEEE

Link

Reference12 articles.

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2. Hybrid Deep Learning (CNN-BiLSTM-LSTM) Model for Prediction of Short Power Consumption;2024 8th International Conference on Smart Cities, Internet of Things and Applications (SCIoT);2024-05-14