LSTM-Based Deep Learning Long Term Electric Demand Prediction for Karnataka-Reference-Cited by-同舟云学术

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LSTM-Based Deep Learning Long Term Electric Demand Prediction for Karnataka

Published:2025-03-28 Issue: Volume: Page:1-6
ISSN:
Container-title:2025 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI)
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Author:

Amosedinakaran S.¹,Sujatha S.²,Jalli Ravi Kumar³,Babu Rao P.¹,K Vinoth Kumar⁴,Saravanan S.⁵

Affiliation:

1. Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology,Department EEE,Chennai,India

2. Sri Sairam College of Engineering,Department EEE,Bangalore

3. GMR Institute of Technology Rajam,Department EEE,Vizianagaram,Andhra Pradesh

4. New Horizon College of Engineering,Department EEE,Bengaluru

5. B. V. Raju Institute of Technology,Department EEE,Medak

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/11011562/11011530/11011862.pdf?arnumber=11011862

Reference15 articles.

1. Principles and algorithms for forecasting groups of time series: Locality and globality

2. Energy Source Expansion Planning for a Real-world Deregulated Electric Utility Considering Emission

3. A hybrid method of exponential smoothing and recurrent neural networks for time series forecasting

4. Understanding machine learning-based forecasting methods: A decomposition framework and research opportunities

5. A Dynamic Factor Machine Learning Method for Multi-variate and Multi-step-Ahead Forecasting

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